Running a function for each group - r

Question

I have following parameters of gompertz
A <- 100 # A is always 100
mu <- 35
lambda <- 265 # day of the year. Also the start day
I can use the above parameters to run a gompertz using following equation
grofit::gompertz(time,A,mu,lambda)
time is a basically a vector of lambda:end.day.
Now the issue is that I know the lambda (start day) but not the end day. I want find the end day when it reaches 100.
For e.g in the above example if I supply lambda:end.day as 265:270, I do not reach 100.
time <- 265:270
x <- round(grofit::gompertz(time,A,mu,lambda),2)
x
6.60 35.00 66.67 85.51 94.13 97.69
By multiple trials, I know if I give a vector of 265:277, I will reach 100.
time <- 265:277
x <- round(grofit::gompertz(time,A,mu,lambda),2)
x
[1] 6.60 35.00 66.67 85.51 94.13 97.69
[7] 99.10 99.65 99.87 99.95 99.98 99.99
[13] 100.00
I have dataframe that has the lambda (same as start day) and mu.
df <- data.frame(id = c(1,1,2,2), year = c(1981,1982,1981,1982), mu= c(35,32,33,28), lambda = c(275,278,284,296))
For each id and year, I want two columns: one column called day first value of which is equal to lamba and a second column which tells me the value of x for each day till it reaches 100 (end day).
How do I implement the above equation for each id and year such that I have a dataframe something like this:
id year day x
1 1981 275 6.6
1 1981 276 35
1 1981 277 66.67
1 1981 278 85.51
1 1981 279 94.13
1 1981 280 97.69
1 1981 281 99.1
1 1981 282 99.65
1 1981 283 99.87
1 1981 284 99.95
1 1981 285 99.98
1 1981 286 99.99
1 1981 287 100
. . . .
. . . .
2 1982 296 8
2 1982 297 33
2 1982 298 45
2 1982 299 63
2 1982 300 61
2 1982 301 73
2 1982 302 81
2 1982 303 91
2 1982 304 94
2 1982 305 98
2 1982 306 99
2 1982 307 100

Answer 1

Using dplyr and tidyr:
library(dplyr)
library(tidyr)
A <- 100 # A is always 100
df <-
data.frame(
id = c(1, 1, 2, 2),
year = c(1981, 1982, 1981, 1982),
mu = c(35, 32, 33, 28),
lambda = c(275, 278, 284, 296)
)
df2 <- df %>%
crossing(day = 1:365) %>%
group_by(id, year) %>%
filter(day >= lambda) %>%
mutate(x = round(grofit::gompertz(day, A, mu, lambda), 2)) %>%
group_by(id, year, x) %>%
filter(x != 100 | row_number() == 1)
df2 %>%
as.data.frame()
Result:
id year mu lambda day x
1 1 1981 35 275 275 6.60
2 1 1981 35 275 276 35.00
3 1 1981 35 275 277 66.67
4 1 1981 35 275 278 85.51
5 1 1981 35 275 279 94.13
6 1 1981 35 275 280 97.69
7 1 1981 35 275 281 99.10
8 1 1981 35 275 282 99.65
9 1 1981 35 275 283 99.87
10 1 1981 35 275 284 99.95
11 1 1981 35 275 285 99.98
12 1 1981 35 275 286 99.99
13 1 1981 35 275 287 100.00
14 1 1982 32 278 278 6.60
15 1 1982 32 278 279 32.01
16 1 1982 32 278 280 62.05
17 1 1982 32 278 281 81.87
18 1 1982 32 278 282 91.96
19 1 1982 32 278 283 96.55
20 1 1982 32 278 284 98.54
21 1 1982 32 278 285 99.39
22 1 1982 32 278 286 99.74
23 1 1982 32 278 287 99.89
24 1 1982 32 278 288 99.95
25 1 1982 32 278 289 99.98
26 1 1982 32 278 290 99.99
27 1 1982 32 278 291 100.00
28 2 1981 33 284 284 6.60
29 2 1981 33 284 285 33.01
30 2 1981 33 284 286 63.64
31 2 1981 33 284 287 83.17
32 2 1981 33 284 288 92.76
33 2 1981 33 284 289 96.98
34 2 1981 33 284 290 98.76
35 2 1981 33 284 291 99.49
36 2 1981 33 284 292 99.79
37 2 1981 33 284 293 99.92
38 2 1981 33 284 294 99.97
39 2 1981 33 284 295 99.99
40 2 1981 33 284 296 99.99
41 2 1981 33 284 297 100.00
42 2 1982 28 296 296 6.60
43 2 1982 28 296 297 28.09
44 2 1982 28 296 298 55.26
45 2 1982 28 296 299 75.80
46 2 1982 28 296 300 87.86
47 2 1982 28 296 301 94.13
48 2 1982 28 296 302 97.21
49 2 1982 28 296 303 98.69
50 2 1982 28 296 304 99.39
51 2 1982 28 296 305 99.71
52 2 1982 28 296 306 99.87
53 2 1982 28 296 307 99.94
54 2 1982 28 296 308 99.97
55 2 1982 28 296 309 99.99
56 2 1982 28 296 310 99.99
57 2 1982 28 296 311 100.00