[Basta-users] errors in inputMat and `colnames<-`(`*tmp*`, value = c("b0", "b1"))?

[Caroline Chong]

Dear BaSTA

Owen, and Fernando - thanks for your assistance with my previous birth-death coding issue (rowSums error)- happy to report that I was able to re-code this successfully and DataCheck now passes with no errors.

However I am running into the below two errors - would you be able to solve or decipher what the issue is? Firstly in the final compiled matrix (im2 = inputMat), every single observation now has a recorded Death observation whereas this is not the case in my input birthDeath matrix. I tried editing this via bd.na (below code) but this didn't work. Is there some possible issue when reading 0s in the birth and death columns?

##e.g. original births and deaths observation matrix
> head(birthDeath)
  ID birth death
1  1     0    68
2  2     0    68
3  3     0     0
4  4     1     0
5  5     1     0
6  6     1     0
## whereas final merged matrix below shows:
> head(im2)
ID birth death 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
1     1     0    53 1 0 0 0 0 0 0 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  0  1  0  0  0  0
10    2     0    99 1 0 0 0 0 0 0 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  0  1  0  0  0  0
100   3     0    99 1 0 0 0 0 0 0 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  0  1  0  0  0  0
1000  4     8   103 0 0 0 0 0 0 0 0 1  0  0  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  0  0
1001  5     8   103 0 0 0 0 0 0 0 0 1  0  0  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  0  0
1002  6     8   103 0 0
> dc <- DataCheck(im2, studyStart = 1, studyEnd = 109, autofix = rep(1, 7), silent=FALSE)
No problems were detected with the data.

*DataSummary*
- Number of individuals         =    1,720
- Number with known birth year  =    1,428
- Number with known death year  =    1,720
- Number with known birth
 AND death years                =    1,428

- Total number of detections
 in recapture matrix            =   10,339

- Earliest detection time       =       1
- Latest detection time         =     109
- Earliest recorded birth year  =       1
- Latest recorded birth year    =     107
- Earliest recorded death year  =       2
- Latest recorded death year    =     109


Secondly on running basta (run time to error 20mins) I get returned e.g.

> out <- basta(object = im2, studyStart = 1, studyEnd = 109)
No problems were detected with the data.

Starting simulation to find jump sd's...  done.

Simulation started...

Error in `colnames<-`(`*tmp*`, value = c("b0", "b1")) :
  length of 'dimnames' [2] not equal to array extent

 It appears that the dimensions of the matrix are not 2 - is this correct?, which I am unsure how to interpret or fix.

looking forward to hearing back,
many thanks for your help,
best regards
Caroline.




cv <- read.csv("~/CaptHist.csv")
rd <- cv$ROBSDATES
class(rd)
sum(is.na(cv))
rd<-as.Date(rd)
Y <- CensusToCaptHist(ID = cv[,1], d=rd, timeInt="D")
head(Y)
sum(is.na(cv))

birthDeath <- read.delim("~/penults_birthdeath.csv", sep=",", header=T)

bd.na <- t( # the below returns a transposed matrix, so we have to re-transpose it back to normal
  apply( # foreach row (hence 1) in the birth dates matrix
    birthDeath, 1,
    function(r) { # apply by row this function (hence r)
      if(r[2] == 0) { # if birth [2] is 0
        r[2] <- NA # replace birth value with NA (R's missing data value)
      }
      if (r[3] == 0) { # if death [3] is 0
        r[3] <- NA # replace death value with NA (R's missing data value)
      }
      return(r) # return the whole row
    }
  ))

table(is.na(bd.na[,3]))
BD <- bd.na
head(BD)
covar <- read.delim("~/fixed_covars.csv", sep=",", header=T)
head(covar)
covMat <- MakeCovMat(x=c("CLADE"), data = covar)
days <- as.numeric(colnames(Y)[2:ncol(Y)])
y <- as.matrix(Y)
bd <- apply(y,1,function(r) min(as.numeric(days[as.logical(r[2:ncol(Y)])]))) -1
dd <- apply(y,1,function(r) max(as.numeric(days[as.logical(r[2:ncol(Y)])])))
inputMat <- as.data.frame(cbind(BD, Y[, -1], covMat[, -1]))
##inputMat <- merge(BD, Y, by.x = "ID", by.y = "ID")
##inputMat <- merge(inputMat, covMat, by.x = "ID", by.y = "ID")
dim(inputMat)
colnames(inputMat)
im2 <- inputMat
im2[,2] <- bd
im2[,3] <- dd
head(im2)
dc <- DataCheck(im2, studyStart = 1, studyEnd = 109, autofix = rep(1, 7), silent=FALSE)
names(dc)
head(inputMat)
# outMat <- dc$newData
out <- basta(object = im2, studyStart = 1, studyEnd = 109)

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