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(v0.7.1.9027) tibble printing

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dr. M.S. (Matthijs) Berends
2019-08-07 15:37:39 +02:00
parent 14c47da656
commit 90c874025a
42 changed files with 946 additions and 602 deletions
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10
R/resistance_predict.R
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@ -28,7 +28,7 @@
#' @param year_max highest year to use in the prediction model, defaults to 10 years after today
#' @param year_every unit of sequence between lowest year found in the data and \code{year_max}
#' @param minimum minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.
#' @param model the statistical model of choice. Defaults to a generalised linear regression model with binomial distribution (i.e. using \code{\link{glm}(..., family = \link{binomial})}), assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See Details for valid options.
#' @param model the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using \code{\link{glm}(..., family = \link{binomial})}), assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See Details for all valid options.
#' @param I_as_S a logical to indicate whether values \code{I} should be treated as \code{S} (will otherwise be treated as \code{R})
#' @param preserve_measurements a logical to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be \code{NA}.
#' @param info a logical to indicate whether textual analysis should be printed with the name and \code{\link{summary}} of the statistical model.
@ -112,7 +112,7 @@ resistance_predict <- function(x,
year_max = NULL,
year_every = 1,
minimum = 30,
model = 'binomial',
model = NULL,
I_as_S = TRUE,
preserve_measurements = TRUE,
info = TRUE,
@ -121,6 +121,10 @@ resistance_predict <- function(x,
if (nrow(x) == 0) {
stop('This table does not contain any observations.')
}
if (is.null(model)) {
stop('Choose a regression model with the `model` parameter, e.g. resistance_predict(..., model = "binomial").')
}
if (!col_ab %in% colnames(x)) {
stop('Column ', col_ab, ' not found.')
@ -252,7 +256,7 @@ resistance_predict <- function(x,
se <- predictmodel$se.fit
} else {
stop('No valid model selected.')
stop('No valid model selected. See ?resistance_predict.')
}
# prepare the output dataframe