plotrcim0: Main Effects Plot for a Row-Column Interaction Model (RCIM)

Description

Produces a main effects plot for Row-Column Interaction Models (RCIMs).

Usage

plotrcim0(object, centered = TRUE, which.plots = c(1, 2),
            hline0 = TRUE, hlty = "dashed", hcol = par()$col, hlwd = par()$lwd,
            rfirst = 1, cfirst = 1,
            rtype = "h", ctype = "h",
            rcex.lab = 1, rcex.axis = 1, rtick = FALSE,
            ccex.lab = 1, ccex.axis = 1, ctick = FALSE,
            rmain = "Row effects", rsub = "",
            rxlab = "", rylab = "Row effects",
            cmain = "Column effects", csub = "",
            cxlab= "", cylab = "Column effects",
            rcol = par()$col, ccol = par()$col,
            no.warning = FALSE, ...)

Arguments

Value

The original object with the post slot assigned additional information from the plot.

Details

This function plots the row and column effects of a rank-0 RCIM. As the result is a main effects plot of a regression analysis, its interpretation when centered = FALSE is relative to the baseline (reference level) of a row and column, and should also be considered in light of the link function used. Many arguments that start with "r" refer to the row effects plot, and "c" for the column effects plot.

Examples

Run this code

alcoff.e <- moffset(alcoff, "6", "Mon", postfix = "*")  # Effective day
fit0 <- rcim(alcoff.e, family = poissonff)
if (FALSE) par(oma = c(0, 0, 4, 0), mfrow = 1:2)  # For all plots below too
ii <- plot(fit0, rcol = "blue", ccol = "orange",
           lwd = 4, ylim = c(-2, 2),  # A common ylim
           cylab = "Effective daily effects", rylab = "Hourly effects",
           rxlab = "Hour", cxlab = "Effective day")
ii@post  # Endowed with additional information


# Negative binomial example
if (FALSE) {
fit1 <- rcim(alcoff.e, negbinomial, trace = TRUE)
plot(fit1, ylim = c(-2, 2)) }

# Univariate normal example
fit2 <- rcim(alcoff.e, uninormal, trace = TRUE)
if (FALSE)  plot(fit2, ylim = c(-200, 400)) 

# Median-polish example
if (FALSE) {
fit3 <- rcim(alcoff.e, alaplace1(tau = 0.5), maxit = 1000, trace = FALSE)
plot(fit3, ylim = c(-200, 250)) }

# Zero-inflated Poisson example on "crashp" (no 0s in alcoff)
if (FALSE) {
cbind(rowSums(crashp))  # Easy to see the data
cbind(colSums(crashp))  # Easy to see the data
fit4 <- rcim(Rcim(crashp, rbaseline = "5", cbaseline = "Sun"),
             zipoissonff, trace = TRUE)
plot(fit4, ylim = c(-3, 3)) }