Error in xy.coords when plotting 1 to 1 plot

I'm trying to run a timeseries analysis using mostly base R functions and forecast package.

All going well until I try to plot a 1 to 1 plot (Observed /Predicted values plot) to visually evaluate the model.

I'm following this series of tutorials
[https://www.youtube.com/watch?v=h0Igk8uOXKc&list=PLD8eCxFKntVETvfPd-diUORGYLAL6idBv&index=39]

but using my own dataset.

The issue I'm having is

# ---- Visual Evaluation of the model
autoplot(arima_forecast, main = "Seasonal Forecasts from ARIMA") + 
# ---- add empirical data to the graph
  autolayer(TotalGen_test)
# ---- more quantitative visualisation: observed-predicted plots
plot(arima_forecast$mean, TotalGen_test, xlab = "Predicted Values", ylab = "Observed Values", 
     main = "Observed v Predicted Plot\nTotal 2019 - 2023")
# ---- convert both time-series objects to vectors before plotting Observed-Predicted / 1 to 1 plot
plot(as.vector(arima_forecast$mean), as.vector(TotalGen_test), xlab = "Predicted Values", ylab = "Observed Values",
     main = "Observed v Predicted Plot\nTotal  2019 - 2023")

The first two plots work as expected but when I try to convert the values to vectors to get a scatterplot/point-estimate plot, it throws a length error:

Error in xy.coords(x, y, xlabel, ylabel, log) : 
  'x' and 'y' lengths differ

Assessing the lengths they are different, but this is not unusual as one is an object of predicted mean values and the plot is comparing these to the original values held within a training set. The training set is going to be different in length, surely this is not an issue?

Unclear, as I'm new to Time-series modelling.

Has anyone come across this before, any workaround? Converting to vector is throwing this off but I need it to work to be able to evaluate.

Hard to know what's going on without seeing your data or a representative toy version of it. To share it, you would run, say, dput(head(arima_forecast, 100)) and paste the output here, like this:

```r
<-- paste output here
```

Is the length of as.vector(arima_forecast$mean) the same as the length of as.vector(TotalGen_test)?

1 Like

No one is 57 one 64. Im on the run but will post dput asap. But the trouble is it plots fine until i change to vector

dput(head(arima_forecast, 100))

list(method = "ARIMA(0,1,1)(0,1,1)[12]", model = structure(list(
    coef = c(ma1 = -0.681953776890434, sma1 = -0.376015845595784
    ), sigma2 = 2442.12135498556, var.coef = structure(c(0.0107529252053473, 
    -0.00396334589980202, -0.00396334589980202, 0.021418766880964
    ), dim = c(2L, 2L), dimnames = list(c("ma1", "sma1"), c("ma1", 
    "sma1"))), mask = c(TRUE, TRUE), loglik = -500.214146351263, 
    aic = 1006.42829270253, arma = c(0L, 1L, 0L, 1L, 12L, 1L, 
    1L), residuals = structure(c(1.52651368629734, 0.458044797256094, 
    0.380995463232282, 0.0141107087008422, -0.01678409189612, 
    -0.110551109416663, -0.0602251834522056, -0.0733307705459409, 
    -0.0206985540314787, 0.105982567190833, 0.285522239636255, 
    -0.642953404322295, -8.49440739329303, -32.4999326610537, 
    1.25563453891637, 23.5063699826618, 86.5158465851581, 50.4524406897683, 
    7.97257584950404, 59.6350271095157, -21.1484081116143, 29.5701196720678, 
    -96.8306789628235, -141.834932268867, -44.8111320905036, 
    124.393275499639, -22.4224593282531, 134.322237100502, 82.6395193607698, 
    22.9150546280456, 39.1744580867073, 20.8619404013015, 4.56560709638979, 
    51.1759277760134, 0.0226336439330703, -114.66837423337, 54.4009420833286, 
    24.9864282795828, 169.096123218996, 75.1163622460217, -15.9014255170792, 
    -64.2010207854529, 38.9057572712385, -11.6002684717572, -5.5140663336336, 
    26.1199307015139, -54.1004658323348, -43.6361789081171, 17.3585263004092, 
    13.3551195337742, -3.71583952751753, -34.5722117627339, 22.212940567345, 
    40.1012880312768, 2.40445196106885, 25.315023894369, 39.1598754589314, 
    -29.0633847071321, -4.83005880897348, 24.1692848928351, 42.1743426923747, 
    29.33188159338, 12.1819646573298, 5.26172881766932, 39.801554789177, 
    35.5239444951603, 0.849079180659663, -13.5198303750602, 6.01167580121811, 
    -8.8662768809625, 11.5886213416458, -38.7711503724587, -32.7826800128095, 
    86.8591411207755, -16.7064853893651, 78.4614056670368, -63.8760601735502, 
    -22.40914046334, -8.07176322941573, 47.1939787346702, -16.088550015885, 
    -36.8468468491742, 48.5027843420044, -25.4729008375775, 18.2430800282822, 
    -58.4923386706046, 36.5563176824385, -43.2836421656417, 1.34479842477472, 
    30.8702902496336, 11.7632659586631, -29.1625563035884, -12.038742099708, 
    1.06067800213085, 42.4095020281657, 60.9058185895613, 12.9265573856805, 
    -50.8567098436218, 63.062725500677, 30.3565702375048, -21.6935351612552, 
    -41.5311132605059, -2.81505202295102, 0.0982874980235011, 
    -2.98171063004474, 31.4524784793501, -31.8762074839347), tsp = c(2010, 
    2018.83333333333, 12), class = "ts"), call = auto.arima(y = TotalGen_train, 
        x = structure(list(x = structure(c(2644, 2354, 2450, 
        2144, 2113, 2008, 2045, 2023, 2070, 2201, 2399, 2653, 
        2546, 2214, 2331, 2050, 2096, 1983, 1992, 2028, 2009, 
        2187, 2260, 2433, 2383, 2222, 2225, 2087, 2099, 1955, 
        1997, 2008, 2001, 2212, 2291, 2375, 2444, 2213, 2408, 
        2174, 2122, 1937, 2053, 2028, 2027, 2250, 2270, 2390, 
        2457, 2232, 2357, 2106, 2125, 1985, 2045, 2058, 2078, 
        2234, 2296, 2446, 2521, 2296, 2418, 2176, 2214, 2073, 
        2119, 2109, 2136, 2300, 2374, 2467, 2526, 2410, 2459, 
        2308, 2215, 2092, 2154, 2202, 2175, 2318, 2459, 2511, 
        2608, 2380, 2534, 2281, 2263, 2162, 2212, 2203, 2202, 
        2364, 2519, 2625, 2680, 2419, 2642, 2402, 2330, 2191, 
        2270, 2277, 2270, 2462, 2548), tsp = c(2010, 2018.83333333333, 
        12), class = "ts")), class = "data.frame", row.names = c(NA, 
        -107L))), series = "TotalGen_train", code = 0L, n.cond = 0L, 
    nobs = 94L, model = list(phi = numeric(0), theta = c(-0.681953776890434, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.376015845595784, 0.256425426074695
    ), Delta = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1), Z = c(1, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 1, -1), a = c(-69.0000000000005, 9.71142913787484, 
    10.7572027678135, 22.4376265151744, -36.7535348051241, 4.75633340995715, 

This could explain the error message.

Could you include the code 1) where it plots fine, 2) where you change to vector, and 3) where it raises an error?

Also, thanks for trying to share your dput() output — it looks like you lost some of it when you copied and pasted.

Plot works from this code -> shows the following:

# ---- more quantitative visualisation: observed-predicted plots
plot(arima_forecast$mean, TotalGen_test, xlab = "Predicted Values", ylab = "Observed Values", 
     main = "Observed v Predicted Plot\nTotal  2019 - 2023")
Change happens here:

# ---- Vectorise to see points
plot(as.vector(arima_forecast$mean), as.vector(TotalGen_test), xlab = "Predicted Values", ylab = "Observed Values",
     main = "Observed v Predicted Plot\nTotal  2019 - 2023")

Error:
Error in xy.coords(x, y, xlabel, ylabel, log) :
'x' and 'y' lengths differ

The dput output is too long, can't post fully. Can post in segments if it helps. Don't really know how to read or debug that output

In that case, you can follow these steps:

  1. run the command
    sink("for-posit.txt")
    (This will create the file "for-posit.txt" and divert all console output to the file.)
  2. run the command
    dput(head(arima_forecast, 100))
    (This will write the dput() output to the file.)
  3. Use Select-all to copy the contents of the file, and paste them here.
  4. Erase the contents of the file.
  5. run the command
    dput(head(TotalGen_test, 100))
  6. Use Select-all to copy the contents of the file, and paste them here.
  7. VERY IMPORTANT: run the command
    sink()
    (This rediverts all output back to the console.)

Without the data, it's generally very difficult to pin down what's going wrong.

list(method = "ARIMA(0,1,1)(0,1,1)[12]", model = structure(list(
coef = c(ma1 = -0.681953776890434, sma1 = -0.376015845595784
), sigma2 = 2442.12135498556, var.coef = structure(c(0.0107529252053473,
-0.00396334589980202, -0.00396334589980202, 0.021418766880964
), dim = c(2L, 2L), dimnames = list(c("ma1", "sma1"), c("ma1",
"sma1"))), mask = c(TRUE, TRUE), loglik = -500.214146351263,
aic = 1006.42829270253, arma = c(0L, 1L, 0L, 1L, 12L, 1L,
1L), residuals = structure(c(1.52651368629734, 0.458044797256094,
0.380995463232282, 0.0141107087008422, -0.01678409189612,
-0.110551109416663, -0.0602251834522056, -0.0733307705459409,
-0.0206985540314787, 0.105982567190833, 0.285522239636255,
-0.642953404322295, -8.49440739329303, -32.4999326610537,
1.25563453891637, 23.5063699826618, 86.5158465851581, 50.4524406897683,
7.97257584950404, 59.6350271095157, -21.1484081116143, 29.5701196720678,
-96.8306789628235, -141.834932268867, -44.8111320905036,
124.393275499639, -22.4224593282531, 134.322237100502, 82.6395193607698,
22.9150546280456, 39.1744580867073, 20.8619404013015, 4.56560709638979,
51.1759277760134, 0.0226336439330703, -114.66837423337, 54.4009420833286,
24.9864282795828, 169.096123218996, 75.1163622460217, -15.9014255170792,
-64.2010207854529, 38.9057572712385, -11.6002684717572, -5.5140663336336,
26.1199307015139, -54.1004658323348, -43.6361789081171, 17.3585263004092,
13.3551195337742, -3.71583952751753, -34.5722117627339, 22.212940567345,
40.1012880312768, 2.40445196106885, 25.315023894369, 39.1598754589314,
-29.0633847071321, -4.83005880897348, 24.1692848928351, 42.1743426923747,
29.33188159338, 12.1819646573298, 5.26172881766932, 39.801554789177,
35.5239444951603, 0.849079180659663, -13.5198303750602, 6.01167580121811,
-8.8662768809625, 11.5886213416458, -38.7711503724587, -32.7826800128095,
86.8591411207755, -16.7064853893651, 78.4614056670368, -63.8760601735502,
-22.40914046334, -8.07176322941573, 47.1939787346702, -16.088550015885,
-36.8468468491742, 48.5027843420044, -25.4729008375775, 18.2430800282822,
-58.4923386706046, 36.5563176824385, -43.2836421656417, 1.34479842477472,
30.8702902496336, 11.7632659586631, -29.1625563035884, -12.038742099708,
1.06067800213085, 42.4095020281657, 60.9058185895613, 12.9265573856805,
-50.8567098436218, 63.062725500677, 30.3565702375048, -21.6935351612552,
-41.5311132605059, -2.81505202295102, 0.0982874980235011,
-2.98171063004474, 31.4524784793501, -31.8762074839347), tsp = c(2010,
2018.83333333333, 12), class = "ts"), call = auto.arima(y = TotalGen_train,
x = structure(list(x = structure(c(2644, 2354, 2450,
2144, 2113, 2008, 2045, 2023, 2070, 2201, 2399, 2653,
2546, 2214, 2331, 2050, 2096, 1983, 1992, 2028, 2009,
2187, 2260, 2433, 2383, 2222, 2225, 2087, 2099, 1955,
1997, 2008, 2001, 2212, 2291, 2375, 2444, 2213, 2408,
2174, 2122, 1937, 2053, 2028, 2027, 2250, 2270, 2390,
2457, 2232, 2357, 2106, 2125, 1985, 2045, 2058, 2078,
2234, 2296, 2446, 2521, 2296, 2418, 2176, 2214, 2073,
2119, 2109, 2136, 2300, 2374, 2467, 2526, 2410, 2459,
2308, 2215, 2092, 2154, 2202, 2175, 2318, 2459, 2511,
2608, 2380, 2534, 2281, 2263, 2162, 2212, 2203, 2202,
2364, 2519, 2625, 2680, 2419, 2642, 2402, 2330, 2191,
2270, 2277, 2270, 2462, 2548), tsp = c(2010, 2018.83333333333,
12), class = "ts")), class = "data.frame", row.names = c(NA,
-107L))), series = "TotalGen_train", code = 0L, n.cond = 0L,
nobs = 94L, model = list(phi = numeric(0), theta = c(-0.681953776890434,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.376015845595784, 0.256425426074695
), Delta = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1), Z = c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, -1), a = c(-69.0000000000005, 9.71142913787484,
10.7572027678135, 22.4376265151744, -36.7535348051241, 4.75633340995715,
15.9413082376097, 10.0535821262344, -9.5911285318071, -0.758808517388421,
1.14637377939144, -12.5912158494307, 20.0511729313444, -8.17386952441082,
2462, 2270, 2277, 2270, 2191, 2330, 2402, 2642, 2419, 2680,
2625, 2519, 2364), P = structure(c(4.44089209850063e-16,
-2.22044604925031e-16, 3.30872245021211e-24, -3.15544362088405e-30,
-5.52202633654708e-30, -5.52202633654708e-30, -9.46633086265214e-30,
-1.10440526730942e-29, -7.88860905221012e-30, -1.73549399148623e-29,
-1.41994962939782e-29, 2.80135930224326e-17, -5.55111512312578e-17,
5.55111512312578e-17, -1.1100883149017e-16, -1.23259516440783e-32,
0, 0, -5.77778983316171e-34, -9.62964972193618e-34, 7.70371977754894e-33,
7.3185337886715e-33, 1.68518870133883e-32, -1.11222454288363e-32,
4.12149008098868e-32, -2.21963120954556e-16, 1.1112211507719e-16,
-2.22044604925031e-16, 1.37221619456174e-07, -9.09548195815649e-08,
-4.90608756715887e-17, -1.56943073021813e-15, -3.08991638770395e-15,
-4.60720112949067e-15, -6.12232300745753e-15, -7.64079737353711e-15,
-9.21128875879133e-15, -1.0631148125803e-14, -1.21703394922549e-14,
-1.36002320516582e-14, -3.89057119853931e-11, 4.32915691083482e-17,
-4.75000916870374e-17, 4.13659013048813e-17, -2.21938659659403e-17,
8.1850475248295e-19, -9.73824233428564e-19, 2.82418421859982e-18,
-7.83827115265285e-19, 3.60728389671844e-19, 2.79079289239983e-19,
-1.97256913717188e-17, 2.49677343934004e-16, 2.38251324423457e-17,
3.30872245021211e-24, -9.09548195815649e-08, 1.46133956366201e-07,
-1.32209457947289e-08, -7.23651097387949e-15, -8.66083192346058e-15,
-1.00843987672779e-14, -1.15098945932995e-14, -1.293383987619e-14,
-1.43574804767278e-14, -1.57820604897397e-14, -1.72061141506968e-14,
-1.86303847523743e-14, -9.60126694218533e-10, -7.92791290571534e-25,
4.57411810198056e-25, 1.07796048447223e-25, -2.08484456874452e-24,
-2.86414471074256e-25, 6.01309694778075e-24, 4.01786295126223e-24,
-3.45535972431309e-24, -5.42274199945653e-24, 3.17940399668128e-18,
4.37337995394001e-17, -4.43274932090532e-24, -1.43789319461397e-24,
-3.15544362088405e-30, -4.90608756715887e-17, -1.32209457947289e-08,
2.84029249564277e-08, -1.32209403049421e-08, -3.40637155089172e-16,
-3.40636738132267e-16, -3.40636354350409e-16, -3.40636006148142e-16,
-3.40635691511837e-16, -3.40635412894558e-16, -3.40635168153231e-16,
-3.4063495825173e-16, 8.26065869302785e-16, 2.92907451037977e-31,
-1.54357783500908e-31, 5.67083950111468e-31, -6.4908476830917e-31,
-4.67154713851992e-31, 2.82818926703218e-31, 1.62784383794132e-30,
3.69103407886044e-31, -6.96787917392153e-19, 2.03439491715659e-18,
2.18767545000482e-30, 7.38269934737513e-30, 4.58436717769221e-30,
-5.52202633654708e-30, -1.56943073021813e-15, -7.23651097387949e-15,
-1.32209403049421e-08, 2.84029247621387e-08, -1.32209404654709e-08,
-5.10955263713213e-16, -5.10954704006828e-16, -5.10954198710335e-16,
-5.10953743165973e-16, -5.10953340710689e-16, -5.10952988961492e-16,
-5.10952690072698e-16, 1.22742954579644e-15, 6.27868386449745e-31,
-9.46739626018429e-31, 7.51534949433534e-31, -1.09786486856013e-30,
7.37972908612728e-32, -9.41524023412034e-32, -5.97017706302362e-31,
2.84001834395305e-17, -1.89716866163318e-18, -1.70949420203341e-30,
2.07574300106054e-30, 9.51853288421577e-30, 4.97693618883642e-30,
-5.52202633654708e-30, -3.08991638770395e-15, -8.66083192346058e-15,
-3.40637155089172e-16, -1.32209404654709e-08, 2.84029245400941e-08,
-1.32209406463576e-08, -6.8127310947742e-16, -6.81272445754882e-16,
-6.81271851688129e-16, -6.81271324830739e-16, -6.81270867505248e-16,
-6.81270479834255e-16, 1.62883680860839e-15, -1.30168797384973e-32,
-1.98981564830428e-30, 2.63750481195498e-31, -7.01728219231143e-31,
-1.22660433616348e-30, -7.34779642630356e-31, -2.76376699408359e-17,
-3.03397817348209e-17, 1.45765413972429e-30, -1.45050719071887e-30,
2.88793754347438e-30, 1.5547773470984e-29, 9.29841813961973e-30,
-9.46633086265214e-30, -4.60720112949067e-15, -1.00843987672779e-14,
-3.40636738132267e-16, -5.10955263713213e-16, -1.32209406463576e-08,
2.84029244290718e-08, -1.32209407923319e-08, -8.51590764135068e-16,
-8.51590027693978e-16, -8.51589379526813e-16, -8.51588815836704e-16,
-8.51588339820641e-16, 2.02904052777804e-15, 9.65458934540233e-32,
-3.63244718596958e-31, 1.24841092619153e-30, -1.52187454323691e-30,
1.25087471349893e-30, -9.4770345020359e-18, 3.11935887355201e-17,
2.90799812702967e-30, -7.98491809692428e-31, -1.895838885934e-30,
2.59689795630698e-30, 1.89603746583942e-29, 1.04522842462987e-29,
-1.10440526730942e-29, -6.12232300745753e-15, -1.15098945932995e-14,
-3.40636354350409e-16, -5.10954704006828e-16, -6.8127310947742e-16,
-1.32209407923319e-08, 2.84029242070272e-08, -1.32209409592281e-08,
-1.02190828818962e-15, -1.02190751577965e-15, -1.02190684687708e-15,
-1.02190628162555e-15, 2.42843100323765e-15, 3.4803445623895e-31,
-7.2863350606067e-31, 3.13120747753732e-30, -1.13947334783483e-30,
8.34517675737069e-19, 8.34781979886286e-19, 2.53124833216669e-30,
1.17752008426021e-33, 3.06535038689386e-30, -2.23698934514786e-30,
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0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0), dim = c(27L, 27L)), V = structure(c(1,
-0.681953776890434, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.376015845595784,
0.256425426074695, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-0.681953776890434, 0.465060953815128, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0.256425426074695, -0.174870287802377, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.376015845595784,
0.256425426074695, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.141387916139112,
-0.0964200234177357, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.256425426074695, -0.174870287802377, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, -0.0964200234177357, 0.0657539991375889, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0), dim = c(27L, 27L)), h = 0, Pn = structure(c(1.00000013734071,
-0.681953870398729, 3.7442731041942e-09, -3.22146674532436e-15,
-4.78669269721698e-15, -6.35208862571813e-15, -7.91279101104766e-15,
-9.47032193310156e-15, -1.10327689188313e-14, -1.26714923408746e-14,
-1.40893326457221e-14, -1.56541446472147e-14, -0.376015845679463,
0.256425426074695, -4.75271548941678e-17, -6.96529490813808e-17,
6.06579253841859e-17, -3.25445312027985e-17, 1.20023494319152e-18,
-1.4279915540414e-18, 4.1413132604155e-18, -1.14938452135736e-18,
5.28963108610528e-19, 4.09234905296624e-19, 1.31473902830054e-18,
-6.67657405994179e-18, 1.46058694732578e-16, -0.681953870398729,
0.465061154701614, -9.35082407661113e-08, 2.14783053794052e-15,
1.69487243273659e-15, 1.24191444078353e-15, 7.88956585037404e-16,
3.35998801752523e-16, -1.16958941454662e-16, -5.69916700016244e-16,
-1.02287451632483e-15, -1.47583245291106e-15, 0.256425426074696,
-0.174870287802377, -5.85379921348902e-31, -6.35312764189676e-31,
8.20711584432079e-31, -1.00770084508184e-30, -2.81308965839243e-31,
9.51303612080699e-31, 1.3654113517798e-30, -6.10085467546869e-31,
-5.43449834183101e-31, -3.66457293218745e-31, -2.06222826174941e-17,
1.02861870198186e-16, 2.1000906645262e-29, 3.7442731041942e-09,
-9.35082407661113e-08, 1.46133956380221e-07, -1.32209457947289e-08,
-7.23651099180217e-15, -8.66083194724453e-15, -1.00843987969055e-14,
-1.1509894628759e-14, -1.29338399174997e-14, -1.43574805241733e-14,
-1.5782060542494e-14, -1.7206114209415e-14, -1.40792445475041e-09,
0, -5.55098588928856e-25, 1.96612182143241e-25, 3.34915855826653e-25,
-2.20670016488003e-24, -2.8192046427496e-25, 6.00775015814627e-24,
4.03336915698961e-24, -3.45966333327172e-24, -5.42076141738786e-24,
3.17940399821357e-18, 4.37337995443228e-17, -3.62665780438215e-24,
-1.30708111702358e-24, -3.22146674532436e-15, 2.14783053794052e-15,
-1.32209457947289e-08, 2.84029249564277e-08, -1.32209403049421e-08,
-3.40637155089152e-16, -3.40636738132242e-16, -3.40636354350379e-16,
-3.40636006148107e-16, -3.40635691511796e-16, -3.40635412894513e-16,

contd in next op
    -3.4063516815318e-16, 8.70687417955798e-16, 0, 8.8403369033258e-32, 
    7.00268448613869e-32, 3.71676487483347e-31, -5.44243657696136e-31, 
    -4.71021230277029e-31, 2.87419153375368e-31, 1.6145027368232e-30, 
    3.72806111390655e-31, -6.96787917392155e-19, 2.03439491715659e-18, 
    2.18344006252806e-30, 6.68916099108947e-30, 4.47182016359429e-30, 
    -4.78669269721698e-15, 1.69487243273659e-15, -7.23651099180217e-15, 
    -1.32209403049421e-08, 2.84029247621387e-08, -1.32209404654709e-08, 
    -5.10955263713175e-16, -5.10954704006783e-16, -5.10954198710282e-16, 
    -5.10953743165912e-16, -5.10953340710622e-16, -5.10952988961417e-16, 
    1.28891936528334e-15, 0, 3.24001150413917e-31, -6.13332409101343e-31, 
    4.61184140845707e-31, -9.42084220112375e-31, 6.8052135812797e-32, 
    -8.73170465365585e-32, -6.1684089752035e-31, 2.84001834395305e-17, 
    -1.89716866163318e-18, -1.71145308349701e-30, 2.06944975021934e-30, 
    8.48802248391729e-30, 4.80970554110181e-30, -6.35208862571813e-15, 
    1.24191444078353e-15, -8.66083194724453e-15, -3.40637155089152e-16, 
    -1.32209404654709e-08, 2.84029245400941e-08, -1.32209406463576e-08, 
    -6.8127310947736e-16, -6.81272445754812e-16, -6.81271851688049e-16, 
    -6.81271324830649e-16, -6.81270867505149e-16, 1.70721516855972e-15, 
    0, -4.16258060204045e-31, -1.54737400346197e-30, -1.21553983779058e-31, 
    -4.95002501140376e-31, -1.23422833384723e-30, -7.25708914968088e-31, 
    -2.7637669940836e-17, -3.03397817348209e-17, 1.45429411964012e-30, 
    -1.45310668674904e-30, 2.87958620579391e-30, 1.41802544330006e-29, 
    9.07649791984793e-30, -7.91279101104766e-15, 7.88956585037404e-16, 
    -1.00843987969055e-14, -3.40636738132242e-16, -5.10955263713175e-16, 
    -1.32209406463576e-08, 2.84029244290718e-08, -1.32209407923319e-08, 
    -8.5159076413498e-16, -8.51590027693878e-16, -8.51589379526702e-16, 
    -8.5158881583658e-16, 2.12374605524875e-15, 0, -4.05771277492455e-31, 
    1.87904435091935e-31, 7.68437505382637e-31, -1.26435650464436e-30, 
    1.24137750653365e-30, -9.47703450203589e-18, 3.11935887355201e-17, 
    2.91709296528941e-30, -8.02677383648567e-31, -1.8990770757693e-30, 
    2.58649470257076e-30, 1.72568574392892e-29, 1.01758384308121e-29, 
    -9.47032193310156e-15, 3.35998801752523e-16, -1.1509894628759e-14, 
    -3.40636354350379e-16, -5.10954704006783e-16, -6.8127310947736e-16, 
    -1.32209407923319e-08, 2.84029242070272e-08, -1.32209409592281e-08, 
    -1.0219082881895e-15, -1.02190751577952e-15, -1.02190684687694e-15, 
    2.5390843398374e-15, 0, -2.5315737541011e-31, -6.8997745264909e-32, 
    2.5567574752504e-30, -8.31266202511852e-31, 8.34517675737058e-19, 
    8.347819798863e-19, 2.49202876775118e-30, 1.20625600314792e-32, 
    3.06034093665258e-30, -2.240864930915e-30, 2.86024026444045e-30, 
    1.95614828557754e-29, 1.0924368116936e-29, -1.10327689188313e-14, 
    -1.16958941454662e-16, -1.29338399174997e-14, -3.40636006148107e-16, 
    -5.10954198710282e-16, -6.81272445754812e-16, -8.5159076413498e-16, 
    -1.32209409592281e-08, 2.84029240960049e-08, -1.32209411609391e-08, 
    -1.19222575313404e-15, -1.19222498357098e-15, 2.95627103425763e-15, 
    0, -6.94837605264239e-32, -9.03210709579214e-31, 1.56398570979211e-30, 
    3.03710889557268e-17, 2.68947337482585e-20, -2.07656523645588e-31, 
    1.65812601567794e-30, 3.87330184657983e-31, -1.52087072847062e-30, 
    -2.86748233902354e-30, 2.72096808794611e-30, 1.77820476319082e-29, 
    1.03999053966342e-29, -1.26714923408746e-14, -5.69916700016244e-16, 
    -1.43574805241733e-14, -3.40635691511796e-16, -5.10953743165912e-16, 
    -6.81271851688049e-16, -8.51590027693878e-16, -1.0219082881895e-15, 
    -1.32209411609391e-08, 2.84029238462047e-08, -1.32209413439836e-08, 
    -1.36254324000213e-15, 3.4021387541043e-15, 0, -6.14037909147185e-31, 
    -2.2179295991084e-30, -7.32687775447509e-17, -6.06876284026291e-17, 
    -1.43082211404554e-30, 1.32451707387583e-30, 4.2451477333997e-31, 
    6.52070163146917e-30, -2.11063602546652e-30, -6.54536350294553e-31, 
    5.10513809877764e-30, 2.90750212139314e-29, 1.48783783241901e-29, 
    -1.40893326457221e-14, -1.02287451632483e-15, -1.5782060542494e-14, 
    -3.40635412894513e-16, -5.10953340710622e-16, -6.81271324830649e-16, 
    -8.51589379526702e-16, -1.02190751577952e-15, -1.19222575313404e-15, 
    -1.32209413439836e-08, 2.84029238184491e-08, -1.32209414918333e-08, 
    3.76495079511678e-15, 0, 2.78874655947272e-30, -6.11427715312144e-18, 
    8.13316236238071e-17, -1.52652130735514e-30, 9.89191171899869e-31, 
    3.37740480531554e-32, -2.36331687060767e-30, 1.86208736049089e-30, 
    8.54186191049362e-30, 3.55001820104558e-30, 6.45590487881188e-30, 
    2.78032455266071e-29, 2.10962080343129e-29, -1.56541446472147e-14, 
    -1.47583245291106e-15, -1.7206114209415e-14, -3.4063516815318e-16, 
    -5.10952988961417e-16, -6.81270867505149e-16, -8.5158881583658e-16, 
    -1.02190684687694e-15, -1.19222498357098e-15, -1.36254324000213e-15, 
    -1.32209414918333e-08, 2.84029235686489e-08, -1.32209357489588e-08, 
    0, 1.10272406424851e-17, -3.63755839442817e-17, 4.6592097214616e-30, 
    -4.68386162474976e-30, 1.47844012180886e-30, -1.10009118423399e-30, 
    7.70371977754894e-32, 2.21713055197859e-30, 1.64012194064017e-30, 
    6.48552093947541e-30, 3.11239908662699e-30, 3.44498792872322e-29, 
    3.90408336649559e-17, -0.376015845679463, 0.256425426074696, 
    -1.40792445475041e-09, 8.70687417955798e-16, 1.28891936528334e-15, 
    1.70721516855972e-15, 2.12374605524875e-15, 2.5390843398374e-15, 
    2.95627103425763e-15, 3.4021387541043e-15, 3.76495079511678e-15, 
    -1.32209357489588e-08, 0.14138792518665, -0.0964200234177357, 
    3.78740711732903e-18, 2.61906089558659e-17, -2.28083379779792e-17, 
    1.22372577417856e-17, -4.51307295195691e-19, 5.3694737807088e-19, 
    -1.55719919397122e-18, 4.32186733453106e-19, -1.98898483293917e-19, 
    -1.53878787861362e-19, -4.94362639677905e-19, -1.4554410140206e-18, 
    -2.72577906281286e-17, 0.256425426074695, -0.174870287802377, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.0964200234177357, 0.0657539991375889, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -4.75271548941678e-17, 
    -5.85379921348902e-31, -5.55098588928856e-25, 8.8403369033258e-32, 
    3.24001150413917e-31, -4.16258060204045e-31, -4.05771277492455e-31, 
    -2.5315737541011e-31, -6.94837605264239e-32, -6.14037909147185e-31, 
    2.78874655947272e-30, 1.10272406424851e-17, 3.78740711732903e-18, 
    0, 1.1100883149017e-16, 9.84691712010596e-34, -3.6959503463888e-33, 
    2.84024563005649e-33, 2.00937499420969e-34, -2.13826368350641e-34, 
    7.17912561814245e-34, 1.00116160764735e-34, 7.17262024901568e-35, 
    -5.11503138389918e-35, -4.89017176283425e-35, -1.11664797514822e-34, 
    -6.15803452800204e-33, -6.96529490813808e-17, -6.35312764189676e-31, 
    1.96612182143241e-25, 7.00268448613869e-32, -6.13332409101343e-31, 
    -1.54737400346197e-30, 1.87904435091935e-31, -6.8997745264909e-32, 
    -9.03210709579214e-31, -2.2179295991084e-30, -6.11427715312144e-18, 
    -3.63755839442817e-17, 2.61906089558659e-17, 0, 9.84691712010596e-34, 
    -1.11013467142907e-16, -4.53280720437711e-33, -1.65288276706655e-32, 
    3.09112007343331e-34, -3.85478517013131e-34, 2.15582983156397e-34, 
    -2.1404586919814e-34, 1.09600222165196e-34, 1.30163946787801e-34, 
    -1.20991714089903e-34, 1.41355573593706e-33, 1.05786603628503e-32, 
    6.06579253841859e-17, 8.20711584432079e-31, 3.34915855826653e-25, 
    3.71676487483347e-31, 4.61184140845707e-31, -1.21553983779058e-31, 
    7.68437505382637e-31, 2.5567574752504e-30, 1.56398570979211e-30, 
    -7.32687775447509e-17, 8.13316236238071e-17, 4.6592097214616e-30, 
    -2.28083379779792e-17, 0, -3.6959503463888e-33, -4.53280720437711e-33, 
    2.22035565601725e-16, 9.03573254089626e-34, 6.14571644275363e-34, 
    2.25718236957976e-34, -1.42788980207307e-33, 4.01379929509493e-34, 
    8.0552627446213e-35, 1.59437777549501e-34, -1.21587046965522e-35, 
    -1.02484749185554e-34, -9.09313064401863e-33, -3.25445312027985e-17, 
    -1.00770084508184e-30, -2.20670016488003e-24, -5.44243657696136e-31, 
    -9.42084220112375e-31, -4.95002501140376e-31, -1.26435650464436e-30, 
    -8.31266202511852e-31, 3.03710889557268e-17, -6.06876284026291e-17, 
    -1.52652130735514e-30, -4.68386162474976e-30, 1.22372577417856e-17, 
    0, 2.84024563005649e-33, -1.65288276706655e-32, 9.03573254089626e-34, 
    -1.11020066067139e-16, 1.02246903212178e-33, 3.03170780641513e-34, 
    1.59650282426327e-33, 8.21207841412089e-35, 1.17643620317561e-34, 
    1.25263145002419e-34, 3.50239842877172e-34, 6.37424801620263e-34, 
    5.38111845608694e-33, 1.20023494319152e-18, -2.81308965839243e-31, 
    -2.8192046427496e-25, -4.71021230277029e-31, 6.8052135812797e-32, 
    -1.23422833384723e-30, 1.24137750653365e-30, 8.34517675737058e-19, 
    2.68947337482585e-20, -1.43082211404554e-30, 9.89191171899869e-31, 
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"Arima")), level = c(80, 95), mean = structure(c(2663.71142913787, 
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2553.80978029502, 2424.86336242125, 2494.27223388944, 2500.51342537205, 
2494.65979915144, 2674.06858330201, 2780.11975623336), tsp = c(2018.91666666667, 
2022.83333333333, 12), class = "ts"), lower = structure(c(2600.37993474134, 
2663.01118726164, 2421.46343398167, 2604.84767687923, 2366.85085493529, 
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2105.45348279506, 2277.74278275147, 2376.82038144443, 2460.93543458768, 
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2133.59552190305, 1995.43690958577, 2055.8271018218, 2053.23142341717, 
2038.71216541297, 2209.61697102075, 2307.31709593033), dim = c(48L, 
2L), dimnames = list(NULL, c("80%", "95%")), tsp = c(2018.91666666667, 
2022.83333333333, 12), class = c("mts", "ts", "matrix")), upper = structure(c(2727.04292353441, 
2795.92607654974, 2560.34908286005, 2749.45777035224, 2516.9672591161, 
2463.56424831208, 2337.18571079814, 2409.08283428283, 2417.73962750044, 
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3017.70917402362, 2784.86954621994, 2976.66420852446, 2746.80925005092, 
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2656.55407272643, 2840.61803737361, 2951.22898540957, 3074.08169880782, 
3146.6456158012, 2914.70892629746, 3107.41376544782, 2878.4732315424, 
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2831.1065226538, 2597.10989356504, 2787.73375001698, 2556.70067118833, 
2504.70349296374, 2379.68430919992, 2452.89863373602, 2462.83416926914, 
2460.572976881, 2643.48028013425, 2752.9430590929, 2887.46246228308, 
2960.51978010929, 2728.96506042758, 2921.95928420286, 2693.23041672927, 
2643.47614606599, 2520.64292444015, 2595.99017942179, 2608.00913239291, 
2607.78501438983, 2792.68591187205, 2904.10139751446, 3036.21636432385, 
3111.01960435096, 2881.20941511629, 3075.94111555756, 2848.93876684774, 
2800.89737436449, 2679.76156907053, 2756.78957240624, 2770.47184320539, 
2771.89317215336, 2958.42144049809, 3071.44618766782, 3202.4062537515, 
3278.57342759956, 3050.14416332782, 3246.26785913266, 3020.66400211702, 
2974.02403868699, 2854.28981525673, 2932.71736595709, 2947.79542732694, 
2950.60743288992, 3138.52019558328, 3252.92241653638), dim = c(48L, 
2L), dimnames = list(NULL, c("80%", "95%")), tsp = c(2018.91666666667, 
2022.83333333333, 12), class = c("mts", "ts", "matrix")), x = structure(c(2644, 
2354, 2450, 2144, 2113, 2008, 2045, 2023, 2070, 2201, 2399, 2653, 
2546, 2214, 2331, 2050, 2096, 1983, 1992, 2028, 2009, 2187, 2260, 
2433, 2383, 2222, 2225, 2087, 2099, 1955, 1997, 2008, 2001, 2212, 
2291, 2375, 2444, 2213, 2408, 2174, 2122, 1937, 2053, 2028, 2027, 
2250, 2270, 2390, 2457, 2232, 2357, 2106, 2125, 1985, 2045, 2058, 
2078, 2234, 2296, 2446, 2521, 2296, 2418, 2176, 2214, 2073, 2119, 
2109, 2136, 2300, 2374, 2467, 2526, 2410, 2459, 2308, 2215, 2092, 
2154, 2202, 2175, 2318, 2459, 2511, 2608, 2380, 2534, 2281, 2263, 
2162, 2212, 2203, 2202, 2364, 2519, 2625, 2680, 2419, 2642, 2402, 
2330, 2191, 2270, 2277, 2270, 2462, 2548), tsp = c(2010, 2018.83333333333, 
12), class = "ts"), series = "TotalGen_train", fitted = structure(c(2642.4734863137, 
2353.54195520274, 2449.61900453677, 2143.9858892913, 2113.0167840919, 
2008.11055110942, 2045.06022518345, 2023.07333077055, 2070.02069855403, 
2200.89401743281, 2398.71447776036, 2653.64295340432, 2554.49440739329, 
2246.49993266105, 2329.74436546108, 2026.49363001734, 2009.48415341484, 
1932.54755931023, 1984.0274241505, 1968.36497289048, 2030.14840811161, 
2157.42988032793, 2356.83067896282, 2574.83493226887, 2427.8111320905, 
2097.60672450036, 2247.42245932825, 1952.6777628995, 2016.36048063923, 
1932.08494537195, 1957.82554191329, 1987.1380595987, 1996.43439290361, 
2160.82407222399, 2290.97736635607, 2489.66837423337, 2389.59905791667, 
2188.01357172042, 2238.903876781, 2098.88363775398, 2137.90142551708, 
2001.20102078545, 2014.09424272876, 2039.60026847176, 2032.51406633363, 
2223.88006929849, 2324.10046583233, 2433.63617890812, 2439.64147369959, 
2218.64488046623, 2360.71583952752, 2140.57221176273, 2102.78705943266, 
1944.89871196872, 2042.59554803893, 2032.68497610563, 2038.84012454107, 
2263.06338470713, 2300.83005880897, 2421.83071510716, 2478.82565730763, 
2266.66811840662, 2405.81803

output from dput(head(TotalGen_test, 100))

structure(c(2793, 2725, 2429, 2550, 2478, 2393, 2255, 2332, 2341, 
2340, 2577, 2711, 2754, 2814, 2694, 2716, 2239, 2260, 2251, 2390, 
2392, 2404, 2622, 2648, 2868, 2859, 2594, 2724, 2513, 2542, 2382, 
2479, 2479, 2486, 2673, 2786, 2910, 2938, 2702, 2851, 2613, 2565, 
2451, 2518, 2536, 2485, 2674, 2788, 3006, 3035, 2684, 2989, 2833, 
2638, 2490, 2582, 2607), tsp = c(2018.91666666667, 2023.58333333333, 
12), class = "ts")

So taking 5 years of monthly data to test prediction 4 years into future


# ---- Split the data
TotalGen_train = window(TotalGen_ts, end = c(2018, 11))
TotalGen_test = window(TotalGen_ts, start = c(2018, 12))

# ---- Fit a seasonal model to the data ( auto.arima finds the best possible arima model)
arima_model = auto.arima(TotalGen_train)
# ---- Make forecasts from it
arima_forecast = forecast(arima_model, h = 48)

You said that running your code one way triggers an error, and running another way doesn't — could you share and label both?

I've included it in one of my responses above with a visual.

But basically the code plots from this point:

# ---- more quantitative visualisation: observed-predicted plots
plot(arima_forecast$mean, TotalGen_test, xlab = "Predicted Values", ylab = "Observed Values", 
     main = "Observed v Predicted Plot\nTotal  2019 - 2023")

Then when I vectorise each argument the error is thrown.

Change happens here:

# ---- Vectorise to see points
plot(as.vector(arima_forecast$mean), as.vector(TotalGen_test), xlab = "Predicted Values", ylab = "Observed Values",
     main = "Observed v Predicted Plot\nTotal  2019 - 2023")

Both arima_forecast$mean and TotalGen_test are time series (ts) objects, which you can see in the dput() output you shared:

# save arima_forecast$mean as af_mean
af_mean <- 
structure(c(2663.71142913787, 
2729.46863190569, 2490.90625842086, 2677.15272361574, 2441.9090570257, 
2385.85036526331, 2256.90394738954, 2326.31281885773, 2332.55401034034, 
2326.70038411973, 2506.1091682703, 2612.16034120165, 2719.69790081511, 
2785.45510358293, 2546.8927300981, 2733.13919529298, 2497.89552870293, 
2441.83683694054, 2312.89041906678, 2382.29929053497, 2388.54048201758, 
2382.68685579697, 2562.09563994754, 2668.14681287889, 2775.68437249235, 
2841.44157526016, 2602.87920177534, 2789.12566697021, 2553.88200038017, 
2497.82330861778, 2368.87689074401, 2438.28576221221, 2444.52695369482, 
2438.67332747421, 2618.08211162478, 2724.13328455612, 2831.67084416959, 
2897.4280469374, 2658.86567345257, 2845.11213864745, 2609.86847205741, 
2553.80978029502, 2424.86336242125, 2494.27223388944, 2500.51342537205, 
2494.65979915144, 2674.06858330201, 2780.11975623336), tsp = c(2018.91666666667, 
2022.83333333333, 12), class = "ts")
# save TotalGen_test as tg_test
tg_test <- 
structure(c(2793, 2725, 2429, 2550, 2478, 2393, 2255, 2332, 2341, 
2340, 2577, 2711, 2754, 2814, 2694, 2716, 2239, 2260, 2251, 2390, 
2392, 2404, 2622, 2648, 2868, 2859, 2594, 2724, 2513, 2542, 2382, 
2479, 2479, 2486, 2673, 2786, 2910, 2938, 2702, 2851, 2613, 2565, 
2451, 2518, 2536, 2485, 2674, 2788, 3006, 3035, 2684, 2989, 2833, 
2638, 2490, 2582, 2607), tsp = c(2018.91666666667, 2023.58333333333, 
12), class = "ts")

The time period for arima_forecast$mean is Dec 2018–Nov 2022:

af_mean
#>           Jan      Feb      Mar      Apr      May      Jun      Jul      Aug
#> 2018                                                                        
#> 2019 2729.469 2490.906 2677.153 2441.909 2385.850 2256.904 2326.313 2332.554
#> 2020 2785.455 2546.893 2733.139 2497.896 2441.837 2312.890 2382.299 2388.540
#> 2021 2841.442 2602.879 2789.126 2553.882 2497.823 2368.877 2438.286 2444.527
#> 2022 2897.428 2658.866 2845.112 2609.868 2553.810 2424.863 2494.272 2500.513
#>           Sep      Oct      Nov      Dec
#> 2018                            2663.711
#> 2019 2326.700 2506.109 2612.160 2719.698
#> 2020 2382.687 2562.096 2668.147 2775.684
#> 2021 2438.673 2618.082 2724.133 2831.671
#> 2022 2494.660 2674.069 2780.120

whereas the time period for TotalGen_test is Dec 2018–Aug 2023:

tg_test
#>       Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
#> 2018                                                        2793
#> 2019 2725 2429 2550 2478 2393 2255 2332 2341 2340 2577 2711 2754
#> 2020 2814 2694 2716 2239 2260 2251 2390 2392 2404 2622 2648 2868
#> 2021 2859 2594 2724 2513 2542 2382 2479 2479 2486 2673 2786 2910
#> 2022 2938 2702 2851 2613 2565 2451 2518 2536 2485 2674 2788 3006
#> 2023 3035 2684 2989 2833 2638 2490 2582 2607

Created on 2024-05-27 with reprex v2.0.2

As time series, operations performed on them will usually only be done on the time period they have in common, namely Dec 2018–Nov 2022, which is why the plot() function works: by restricting to the common time period, both the x and y inputs are cropped to have the same length.

When you apply as.vector() to the time series, the time dimension is stripped away, so that only the underlying vectors are left. This means the plot() function no longer "knows" which values of x to match to which values of y since the vectors are not the same length, and triggers an error.

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