#1

Hello,
i'm a beginner and not able to export the full result of a command.
I'm trying to estimate an Ro of the current epidemic.
So, here an example
library(R0)
epid.count = c(1,1,4,5,8,12,27,38,43,52,66,100)
GT.x <- generation.time("gamma", c(2,1.5))
res.R <- estimate.R(epid.count, GT=GT.x, methods=c("EG","ML","SB","TD"))
print(res.R)

At this point I'm not able to see all the results.
Reproduction number estimate using Exponential Growth method.
R : 2.287246[ 2.086577 , 2.512827 ]

Reproduction number estimate using Maximum Likelihood method.
R : 1.885677[ 1.622073 , 2.176419 ]

Reproduction number estimate using Time-Dependent method.
3.486779 3.811135 2.458036 2.446274 2.48364 2.521225 1.95077 1.647686 1.631888 1.721446 ...Here Stops

Reproduction number estimate using Sequential Bayesian method.
1 3.05 2.14 2.1 2.02 2.36 2.1 1.81 1.7 1.66 ... Here Stops

I tried to export the results but I can see only wht is already displayed in the Console:
cat("Tests Output", file = "tests.txt")
capture.output(res.R, file = "tests.txt", append = TRUE)

Thanks for your help!

#2

The documentation for estimate.R says the results for each method are stored in the estimates component of res.R. You can see the structure of that by running

str(res.R$estimates)

If res.R$estimates is a data frame, you can see the results with

View(res.R$estimates)

If res.R$estimates is itself a list then I would guess that the result of each method is stored with a name related to the method, maybe res.R$estimates$EG for exponential growth. So, start with the str() function I mentioned and post the results here if you get stuck.

#3

This is the result of using str(res.R$estimates) for the time-dipendent method (TD).
It actually shows the results but still without the full serie of R (in my example 12).

> str(res.R$estimates$TD)
List of 16

  • $ R : Named num [1:12] 3.49 3.81 2.46 2.45 2.48 ...*
  • ..- attr(, "names")= chr [1:12] "1" "2" "3" "4" ...
  • $ conf.int :'data.frame': 12 obs. of 2 variables:*
  • ..$ lower: num [1:12] 1 1 1.25 1.4 1.64 ...*
  • ..$ upper: num [1:12] 6 7 3.76 3.61 3.4 ...*
  • $ P : num [1:12, 1:12] 0 0 0 0 0 0 0 0 0 0 ...*
  • $ p : num [1:12, 1:12] 0 0 0 0 0 0 0 0 0 0 ...*
  • $ GT :List of 4*
  • ..$ GT : num [1:14] 0 0.3905 0.2855 0.1626 0.0841 ...*
  • ..$ time: int [1:14] 0 1 2 3 4 5 6 7 8 9 ...*
  • ..$ mean: num 2.24*
  • ..$ sd : num 1.45*
  • ..- attr(, "class")= chr "R0.GT"
  • $ epid :List of 2*
  • ..$ incid: num [1:12] 1 1 4 5 8 12 27 38 43 52 ...*
  • ..$ t : num [1:12] 1 2 3 4 5 6 7 8 9 10 ...*
  • $ import : num [1:12] 0 0 0 0 0 0 0 0 0 0 ...*
  • $ pred : num [1:12] 1 1.36 2.48 5.49 8.5 ...*
  • $ begin : num 1*
  • $ begin.nb : int 1*
  • $ end : int(0) *
  • $ end.nb : int 12*
  • $ data.name : chr "c(1, 1, 4, 5, 8, 12, 27, 38, 43, 52, 66, 100)"*
  • $ call : language est.R0.TD(epid = c(1, 1, 4, 5, 8, 12, 27, 38, 43, 52, 66, 100), GT = list(GT = c(0, 0.39053614575831, 0.285454662| truncated ...*
  • $ method : chr "Time-Dependent"*
  • $ method.code: chr "TD"*
    • attr(, "class")= chr "R0.R"

While View(res.R$estimates$TD) report the following error:
Error in as.data.frame.default(x) : cannot coerce class ‘"R0.R"’ to a data.frame

#4

I should have suggested that you try

summary(res.R)

to get your information. If that does not work, then I don't have anything else to suggest other than extracting individual parts of objects like res.R$estimates$TD. I am sorry I can't suggest anything more specific. I am not familiar with this package.

1 Like
#5

I find the solution.
Typing:

summary(res.R$estimates$TD)
Length Class Mode
R 12 -none- numeric
conf.int 2 data.frame list
P 144 -none- numeric
p 144 -none- numeric
GT 4 R0.GT list
epid 2 -none- list
import 12 -none- numeric
pred 12 -none- numeric
begin 1 -none- numeric
begin.nb 1 -none- numeric
end 0 -none- numeric
end.nb 1 -none- numeric
data.name 1 -none- character
call 9 -none- call
method 1 -none- character
method.code 1 -none- character

Then using list it shows the full serie of R anc confindent interval

list(res.R$estimates$TD$R)
[[1]]
1 2 3 4 5 6 7 8
3.486779 3.811135 2.458036 2.446274 2.483640 2.521225 1.950770 1.647686
9 10 11 12
1.631888 1.721446 1.913671 0.000000

list(res.R$estimates$TD$conf.int)
[[1]]
lower upper
1 1.000234 6.001405
2 1.000604 7.004231
3 1.251801 3.755404
4 1.404649 3.611953
5 1.637209 3.400357
6 1.862050 3.219928
7 1.536986 2.382329
8 1.312000 1.996522
9 1.303383 1.968940
10 1.393965 2.048987
11 1.551868 2.289006
12 0.000000 0.000000

Thanks for your help, I really appreciate it!
Giovanni

#6

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