multreg.plot: A regression function created to allow for easy regression...

In kevinlzheng/RegR: Collective Functions to Perform Generalized Linear Model Graphs

Description

A regression function created to allow for easy regression related functional performance

Usage

multreg.plot(data, yvar = "MBISQ", xvar, j = j, xvar2 = NULL,
  jneg = TRUE, xlim = NULL, x2lim = NULL, binom = TRUE, addcor = F,
  addpred = F, addref = TRUE, ylim = NULL, xlab = names(data[xvar]),
  x2lab = names(data[xvar2]), ln.col = "red",
  ylab = "Probability of Meeting Biological Criterion", cex.lab = 1,
  cex = 1, cex.axis = 1, las = 1, pch = 21, col = 1, bg = 8,
  main = "", type = "p", cex.main = 1, varlist = NULL, varpred,
  cont = TRUE, cont2 = FALSE, xlog = TRUE, x2log = TRUE, add = F,
  rounder = 2, nbin = 41, LC50.plot = FALSE, model.sel = NULL, ...)

Arguments

data	A input data frame, default to be NULL,
yvar	for column index of x, y values in data data frame, or column names; y could be binary
xvar	x variable, either column name or index value
j	threshold for logistic regression
binom	if binomial function will be used
xlog	if xvar should be log transformed
rounder	if x should be round to a value
model.sel	= 0 (single var) 1 (2 var), 2 (2 var interaction),3(quadratic)
x.add	1 to convert percent x value = 0 to 1+ x value , or 100, then *100+1,
x2var	x variable, either column name or index value
xlog2	if xvar2 should be log transformed
add:	add multiple regression lines in single graphs espeically for logistic, regression single x variable
addcor:	add principal component line between two explanatory variables and the predicted line for xvar
addref:	add reference value for one variable to predict the other, e.g, add reference value for habitat(160) to predict cond
nbin:	logistic regression number of bins.
LC50.plot:	to add the biological response variable plot
varlist:	additional variables to include in the multiple regression plot, all these variables should be normal distributed
varpred:	additional variable values for making predictions
jneg:	xvar and yvar are negatively correlated, default is true
cont:	if true plot contour, if not plot scatterplot
cont2:	if true plot contour, if not plot scatterplot

Value

Returns

Examples

set.seed(1)
x <- rlnorm(n) + 1:n
x <- (x - min(x))/max(x)
y <- n + 1:n + (rnorm(n))*0.2*n
par(mfrow=c(1,2))
plot(y~x)
scatter.plot(data = data.frame(x,y), xvar= "x", yvar = "y", add.fit = "linear", xlim = c(0,n), 
    ylim = range(y), log.flag = "x", x.add =100)

kevinlzheng/RegR documentation built on May 20, 2019, 9:07 a.m.