multiplots: plot multiple color graphs

Usage Arguments

View source: R/multiplots.r

Usage

1
2
3
4
5
6
7
multiplots(my.data = my.data, xvar, yvar, classes,
  xlab = names(my.data[xvar]), fit = "loess", log = "",
  ylab = names(my.data[yvar]), type = "n", pos = "topleft", cols = 1:20,
  pchs = 1:20, rounder1 = 2, rounder2 = 2, ltys = 1:20, main = "",
  rounder = 2, interval = "prediction", level = 0.5, predx = 100,
  add.pt = TRUE, add.ln = FALSE, lty = 1, cex = 1, las = 1,
  cex1 = 1, ...)

Arguments

my.data

data frame

xvar

x variable, either column name or index value

yvar

y variable, either column name or index value

classes

group and a factor variable

fit

fitted line, either loess or linear or none

cols

colors for different classes

pchs

point type

ltys

line types for different groups

interval

"prediction" or "confidence" interval

predx

predicted value at 100

\item

add.ptadd predicted point

\item

add.lnadd fitted lines

The output of this function to return 1.Weighted Average, 2. cdf_Abundance based, 3. cdf_ presence/absence based; 4. ecdf weighted, 5. cdf weight new; 6. Linear logistic regression, 7. quadratic logistic 8. GAM 5~7 using full data range; 9~11. repeat 6~8 but uses observed range for each single taxon; 12 Count. 13. Raw quantiles set.seed(1) n = 50 x <- rlnorm(n) + 1:n x <- (x - min(x))/max(x) y <- n + 1:n + (rnorm(n))*0.2*n g <- paste0("g", sample(1:5, n)) par(mfrow=c(1,2)) plot(y~x) multiplots(data = data.frame(x,y, g), xvar= "x", yvar = "y", classes = "g", fit = "linear") change interval, plot, point, regression scatter


kevinlzheng/RegR documentation built on May 18, 2017, 7:31 p.m.