warnErrList {utils} | R Documentation

## Collect and Summarize Errors From List

### Description

Collect errors (class `"error"`, typically from `tryCatch`) from a list `x` into a “summary warning”, by default produce a `warning` and keep that message as `"warningMsg"` attribute.

### Usage

    warnErrList(x, warn = TRUE, errValue = NULL)

### Arguments

`x` | a `list`, typically from applying models to a list of data (sub)sets, e.g., using `tryCatch(*, error = identity)`.
`warn` | logical indicating if `warning()` should be called.
`errValue` | the value with which errors should be replaced.

### Value

a `list` of the same length and names as the `x` argument, with the error components replaced by `errValue`, `NULL` by default, and summarized in the `"warningMsg"` attribute.

### See Also

The `warnErrList()` utility has been used in `lmList()` and `nlsList()` in recommended package nlme forever.

### Examples

    ## Regression for each Chick:
    ChWtgrps <- split(ChickWeight, ChickWeight[,"Chick"])
    sapply(ChWtgrps, nrow)# typically 12 obs.
    nlis1 <- lapply(ChWtgrps, function(DAT) tryCatch(error = identity,
                          lm(weight ~ (Time + I(Time^2)) * Diet, data = DAT)))
    nl1 <- warnErrList(nlis1) #-> warning :
    ## 50 times the same error (as Diet has only one level in each group)
    stopifnot(sapply(nl1, is.null)) ## all errors --> all replaced by NULL
    nlis2 <- lapply(ChWtgrps, function(DAT) tryCatch(error = identity,
                          lm(weight ~ Time + I(Time^2), data = DAT)))
    nl2 <- warnErrList(nlis2)
    stopifnot(identical(nl2, nlis2)) # because there was *no* error at all
    nlis3 <- lapply(ChWtgrps, function(DAT) tryCatch(error = identity,
                          lm(weight ~ poly(Time, 3), data = DAT)))
    nl3 <- warnErrList(nlis3) # 1 error caught:
    stopifnot(inherits(nlis3[[1]], "error")
            , identical(nl3[-1], nlis3[-1])
            , is.null(nl3[[1]])
    )

    ## With different error messages
    if(requireNamespace("nlme")) { # almost always, as it is recommended
     data(Soybean, package="nlme")
     attr(Soybean, "formula") #-> weight ~ Time | Plot  => split by "Plot":
     L <- lapply(split(Soybean, Soybean[,"Plot"]),
                 function(DD) tryCatch(error = identity,
                     nls(weight ~ SSlogis(Time, Asym, xmid, scal), data = DD)))
     Lw <- warnErrList(L)
    } # if <nlme>

[Package utils version 3.5.1 Index]