Hello.
I think you can definitely help me
I have a very important question. I wanna sum data with previous one times a parameter (1/2)^i
Here is an exemple and i insert a picture to explain.
A B
2 2
4 5 i.e (4+1/22)
6 8.5 i.e [6+ 1/2 4 + (1/2)^2 2]
8 12.25 i.e [8+ 1/26 + (1/2)^2 *4 + (1/2)^3 *2]
And so on.
I have 366 observations in the columns.
Thank you in advance.
Merci encore
suppressPackageStartupMessages(library(dplyr))
mtcars %>% select(mpg) %>% mutate(lagged = mpg * (0.5*row_number() * lag(mpg)))
#> mpg lagged
#> 1 21.0 NA
#> 2 21.0 441.000
#> 3 22.8 718.200
#> 4 21.4 975.840
#> 5 18.7 1000.450
#> 6 18.1 1015.410
#> 7 14.3 905.905
#> 8 24.4 1395.680
#> 9 22.8 2503.440
#> 10 19.2 2188.800
#> 11 17.8 1879.680
#> 12 16.4 1751.520
#> 13 17.3 1844.180
#> 14 15.2 1840.720
#> 15 10.4 1185.600
#> 16 10.4 865.280
#> 17 14.7 1299.480
#> 18 32.4 4286.520
#> 19 30.4 9357.120
#> 20 33.9 10305.600
#> 21 21.5 7652.925
#> 22 15.5 3665.750
#> 23 15.2 2709.400
#> 24 13.3 2425.920
#> 25 19.2 3192.000
#> 26 27.3 6814.080
#> 27 26.0 9582.300
#> 28 30.4 11065.600
#> 29 15.8 6964.640
#> 30 19.7 4668.900
#> 31 15.0 4580.250
#> 32 21.4 5136.000
Created on 2020-07-24 by the reprex package (v0.3.0)
Hello.
I thank you for your answer. It's very near to what i wanted. But the operation is not what I meant.
Let us consider your exemple, Every "lagged" value must be exactly the mpg + the half of the previous "lagged".
The first lagged should be 21
The second one should be 21 added to half of the first 21 = 31.5
The third one should be 22.8 added to half of 31.5 = 36.75
The fourth one should be 21.4 added to half of 36.75 = 39.775
And so on
THank you in advance
So, how would you change
lagged = mpg * (0.5*row_number() * lag(mpg))
the thing is,
on each observation should be added ALL the past ones times (0.5) with the row range as exponent.
How would you combine sum, lag and row_number functions to add the value of the first row of column X through the current row of column Y?
Right, the first row X=Y
Because there is no lag and row_number=1
Y_1= X_1
Y_2=X_2+ (1/2)^1X_1
Y_3=X_3 + (1/2)^1X_2 +(1/2)^2 * X_1
And so on
In each case it ends up with X_1
And also Y_4=X_4 + (1/2)^1 X_3 + (1/2)^2 X_2 + (1/2)^3 * X_1
Another way we can do it,
Maybe easier:
Y_1 =X_1
Y_2= X_2 + (1/2)Y_1
Y_3= X_3+ (1/2) Y_2
Y_4=X_4+ (1/2)* Y_3
Y_5= X_5+ (1/2)* Y_4
X_2 is not based on any previous value, but is given by the user?
We already have all the X_i
We just need the Y_i
Personally, I have data X_1 to X_366
And I want to obtain the Y_1 to Y_366
Where Y_1=X_1
Thanks for clarifying
As I told you, I have 366 observations
Y_1 =X_1
Y_2= X_2 + (1/2)Y_1
Y_3= X_3+ (1/2) Y_2
Y_4=X_4+ (1/2)* Y_3
Y_5= X_5+ (1/2)* Y_4
. .
. .
. .
. .
. .
. .
Y_366=X_366+ (1/2)*Y_365
options(scipen=999)
sum_nextx <- function(xvec,i){
results <- vector(length=length(xvec))
y<-0
for (index in seq_along(results)) {
y <- xvec[index] + y * (1/2) ^ i
results[index] <- y
cat(index, "\t", round(y,5),"\n")
}
results
}
r<- sum_nextx((1:10),.5)
Good Morning Nirgrahamuk
sorry, it does not work.
where do I have to put my vector of data? my data is DF.NS$Lunenburg
it does not work
can you please explain a little?
I already have a column of data (Lunenburg) in the dataframe (DF):
for each observation in Lunenburg (X_i) I would like to get the response (Y_i) as defined below.
I tried your code but it does not work.