I have the following table for 27 days. (column days_in_chamber). It corresponds to a negative exponential curve that I created with the following function:
nls(perc ~ SSasymp(daysinchambers, Asym, R0, lrc), data = exp_perc_prvi)
I already fitted this a model that yielded a asym, lrc and r0 values.
Now, I want to predict values with those coefficients for 7 more days. Therefore, I should have 7 new values in the first column for days 28, 29 ... until 34.
Here's the data set:
dput(prvi_cut) structure(list(Prvi_Dro1_B3_R15_perc = c(100, NA, 93.6663935183579, 90.0585704623119, 86.7818450917892, 83.6078741753943, 80.3996517742901, 77.8764590673719, 75.3190148757444, 73.2867601163261, 71.1403337412101, 69.3478393747569, 67.6466823008618, 65.934108065397, 64.3585397687693, 62.7601371490021, 61.2302374986535, 59.8715952718514, 58.3645299446423, 56.9830533947007, 55.6472454910381, 54.4256092030731, 53.2496415613873, 52.14217688912, 51.0118778937132, 50.1099221297017, 48.6371082872019, 48.2375076322601), daysinchambers = 0:27), class = "data.frame", row.names = c("136", "137", "138", "139", "140", "141", "142", "143", "144", "145", "146", "147", "148", "149", "150", "151", "152", "153", "154", "155", "156", "157", "158", "159", "160", "161", "162", "163" )) .
Here's the model output:
dput(modelcut)
structure(list(id = "Prvi_Dro1_B3_R14_perc", Asym = 24.8385975483755,
R0 = 100.000000546026, lrc = -2.90002359059106), row.names = c(NA,
-1L), class = c("tbl_df", "tbl", "data.frame"))
If someone could help me, it would be great!