Format Objects to LaTeX or HTML
Functions to format various objects following model selection and multimodel inference to LaTeX or HTML tables. These functions extend the methods from the xtable package (Dahl 2014).
1.1
## S3 method for class 'aictab' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, include.AICc = TRUE, include.LL = TRUE, include.Cum.Wt = FALSE, ...) ## S3 method for class 'anovaOD' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, ...) ## S3 method for class 'bictab' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, include.BIC = TRUE, include.LL = TRUE, include.Cum.Wt = FALSE, ...) ## S3 method for class 'boot.wt' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, include.AICc = TRUE, include.AICcWt = FALSE, ...) ## S3 method for class 'countDist' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, table.countDist = "distance", ...) ## S3 method for class 'checkParms' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, include.variable = TRUE, include.max.se = TRUE, include.n.high.se = TRUE, ...) ## S3 method for class 'countHist' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, table.countHist = "count", ...) ## S3 method for class 'detHist' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, table.detHist = "freq", ...) ## S3 method for class 'detTime' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, table.detTime = "freq", ...) ## S3 method for class 'dictab' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, include.DIC = TRUE, include.Cum.Wt = FALSE, ...) ## S3 method for class 'ictab' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, include.IC = TRUE, include.Cum.Wt = FALSE, ...) ## S3 method for class 'mb.chisq' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, include.detection.histories = TRUE, ...) ## S3 method for class 'modavg' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, print.table = FALSE, ...) ## S3 method for class 'modavgCustom' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, print.table = FALSE, ...) ## S3 method for class 'modavgEffect' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, print.table = FALSE, ...) ## S3 method for class 'modavgIC' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, print.table = FALSE, ...) ## S3 method for class 'modavgPred' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, ...) ## S3 method for class 'modavgShrink' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, print.table = FALSE, ...) ## S3 method for class 'multComp' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, print.table = FALSE, ...) ## S3 method for class 'summaryOD' xtable(x, caption = NULL, label = NULL, align = NULL, digits = NULL, display = NULL, auto = FALSE, nice.names = TRUE, ...)
x: an object of class aictab, anovaOD, bictab, boot.wt, checkParms, countDist, countHist, detHist, detTime, dictab, ictab, mb.chisq, modavg, modavgEffect, modavgCustom, modavgIC, modavgPred, modavgShrink, multComp, or summaryOD.caption: a character vector of length 1 or 2 storing the caption or title of the table. If the vector is of length 2, the second item is the short caption used when LaTeX generates a list of tables. The default value is NULL and suppresses the caption.label: a character vector storing the LaTeX label or HTML anchor. The default value is NULL and suppresses the label.align: a character vector of length equal to the number of columns of the table specifying the alignment of the elements. Note that the rownames are considered as an additional column and require an alignment value.digits: a numeric vector of length one or equal to the number of columns in the table (including the rownames) specifying the number of digits to display in each column.display: a character vector of length equal to the number of columns (including the rownames) specifying the format of each column. For example, use s for strings, f for numbers in the regular format, or d for integers. See formatC for additional possible values.auto: Logical, indicating whether to apply automatic format when no value is passed to align, digits, or display. This autoformat (based on xalign, xdigits, and xdisplay) can be useful to quickly format a typical matrix or data.frame. Default value is FALSE.nice.names: logical. If TRUE, column labels are modified to improve their appearance in the table. If FALSE, simpler labels are used, or the ones supplied directly by the user in the object storing the output.include.AICc: logical. If TRUE, the column containing the information criterion (AIC, AICc, QAIC, or QAICc) of each model is printed in the table. If FALSE, the column is suppressed.include.BIC: logical. If TRUE, the column containing the information criterion (BIC or QBIC) of each model is printed in the table. If FALSE, the column is suppressed.include.DIC: logical. If TRUE, the column containing the deviance information criterion (DIC) of each model is printed in the table. If FALSE, the column is suppressed.include.IC: logical. If TRUE, the column containing the information criterion of each model is printed in the table. If FALSE, the column is suppressed.include.LL: logical. If TRUE, the column containing the log-likelihood of each model is printed in the table. If FALSE, the column is suppressed.include.Cum.Wt: logical. If TRUE, the column containing the cumulative Akaike weights is printed in the table. If FALSE, the column is suppressed.include.AICcWt: logical. If TRUE, the column containing the Akaike weight of each model is printed in the table. If FALSE, the column is suppressed.include.detection.histories: logical. If TRUE, the column containing detection histories is printed in the table. If FALSE, the column is suppressed.include.variable: logical. If TRUE, the column containing the variable name is printed in the table. If FALSE, the column is suppressed.include.max.se: logical. If TRUE, the column containing the maximum SE in the model is printed in the table. If FALSE, the column is suppressed.include.n.high.se: logical. If TRUE, the column containing the number of SE's greater than the threshold specified by the user is printed in the table. If FALSE, the column is suppressed.print.table: logical. If TRUE, the model selection table is printed and other sections of the output are suppressed (e.g., model-averaged estimates). If FALSE, the model selection table is suppressed and only the other portion of the output is printed in the table.table.detHist: character string specifying, either "freq", "prop", or "hist". If table.type = "freq", the function returns a table of frequencies of sites sampled, of sites with at least one detection, and for data with multiple primary periods, the frequencies of sites with observed extinctions and colonizations. If table.type = "prop", the table returns the proportion of sites with at least one detection, and for data with multiple periods, the proportion of sites with observed extinctions and colonizations. If table.type = "hist", the function returns the frequencies of each observed detection history.table.detTime: character string specifying, either "freq", "prop", or "dist". If table.type = "freq", the function returns a table of frequencies of sites sampled, of sites with at least one detection, and for data with multiple primary periods, the frequencies of sites with observed extinctions and colonizations. If table.type = "prop", the table returns the proportion of sites with at least one detection, and for data with multiple periods, the proportion of sites with observed extinctions and colonizations. If table.type = "dist", the function returns the quantiles of detection times.table.countDist: character string specifying, either "distance", "count", "freq", or "prop". If table.type = "distance", the function returns a table of counts summarized for each distance class. If table.type = "count", the function returns the table of frequencies of counts observed across sites. If table.type = "freq", the function returns a table of frequencies of sites sampled, of sites with at least one detection, and for data with multiple primary periods, the frequencies of sites with observed extinctions and colonizations. If table.type = "prop", the table returns the proportion of sites with at least one detection, and for data with multiple periods, the proportion of sites with observed extinctions and colonizations.table.countHist: character string specifying, either "count", "freq", "prop", or "hist". If table.type = "count", the function returns the table of frequencies of counts observed across sites. If table.type = "freq", the function returns a table of frequencies of sites sampled, of sites with at least one detection, and for data with multiple primary periods, the frequencies of sites with observed extinctions and colonizations. If table.type = "prop", the table returns the proportion of sites with at least one detection, and for data with multiple periods, the proportion of sites with observed extinctions and colonizations. If table.type = "hist", the function returns the frequencies of each observed count history....: additional arguments passed to the function.xtable creates an object of the xtable class inheriting from the data.frame class. This object can then be used with print.xtable for added flexibility such as suppressing row names, modifying caption placement, and format tables in LaTeX or HTML format.
Dahl, D. B. (2014) xtable: Export tables to LaTeX or HTML. R package version 1.7-3. https://cran.r-project.org/package=xtable.
Marc J. Mazerolle
aictab, boot.wt, dictab, formatC, ictab, mb.chisq, modavg, modavgCustom, modavgIC, modavgEffect, modavgPred, modavgShrink, multComp, summaryOD, anovaOD, xtable, print.xtable
if(require(xtable)) { ##model selection example data(dry.frog) ##setup candidate models Cand.models <- list( ) Cand.models[[1]] <- lm(log_Mass_lost ~ Shade + Substrate + cent_Initial_mass + Initial_mass2, data = dry.frog) Cand.models[[2]] <- lm(log_Mass_lost ~ Shade + Substrate + cent_Initial_mass + Initial_mass2 + Shade:Substrate, data = dry.frog) Cand.models[[3]] <- lm(log_Mass_lost ~ cent_Initial_mass + Initial_mass2, data = dry.frog) Model.names <- c("additive", "interaction", "no shade") ##model selection table - AICc out <- aictab(cand.set = Cand.models, modnames = Model.names) xtable(out) ##exclude AICc and LL xtable(out, include.AICc = FALSE, include.LL = FALSE) ##remove row names and add caption print(xtable(out, caption = "Model selection based on AICc"), include.rownames = FALSE, caption.placement = "top") ##model selection table - BIC out2 <- bictab(cand.set = Cand.models, modnames = Model.names) xtable(out2) ##exclude AICc and LL xtable(out2, include.BIC = FALSE, include.LL = FALSE) ##remove row names and add caption print(xtable(out2, caption = "Model selection based on BIC"), include.rownames = FALSE, caption.placement = "top") ##model-averaged estimate of Initial_mass2 mavg.mass <- modavg(cand.set = Cand.models, parm = "Initial_mass2", modnames = Model.names) #model-averaged estimate xtable(mavg.mass, print.table = FALSE) #table with contribution of each model xtable(mavg.mass, print.table = TRUE) ##model-averaged predictions for first 10 observations preds <- modavgPred(cand.set = Cand.models, modnames = Model.names, newdata = dry.frog[1:10, ]) xtable(preds) } ##example of diagnostics ## Not run: if(require(unmarked)){ ##distance sampling example from ?distsamp data(linetran) ltUMF <- with(linetran, { unmarkedFrameDS(y = cbind(dc1, dc2, dc3, dc4), siteCovs = data.frame(Length, area, habitat), dist.breaks = c(0, 5, 10, 15, 20), tlength = linetran$Length * 1000, survey = "line", unitsIn = "m") }) ##summarize counts across distance classes xtable(countDist(ltUMF), table.countDist = "distance") ##summarize counts across all sites xtable(countDist(ltUMF), table.countDist = "count") ##Half-normal detection function fm1 <- distsamp(~ 1 ~ 1, ltUMF) ##determine parameters with highest SE's xtable(checkParms(fm1)) } ## End(Not run)
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