search for: fplot

The example below creates parallel time-series plots of three different y variables conditioned by a dichotomous factor. In the graphical layout, ? Each y variable inhabits its own row and is plotted on its own distinct scale. ? Each level of the factor has its own column, but within each row the scale is held constant across columns. ? The panels fit tightly (as they do

...just spent some time fitting poly functions to time series data in R using lm() and predict(). I want to analyze the functions once I've fit them to the various data I'm studying. However, after pulling the first function into Octave (just by plotting the polynomial function using fplot() over the same x interval as my original data) I was surprised to see that the scale and y values were vastly different than the ones I have in R. The basic shape of the polynomial over the same interval looks similar in both Octave and R, but the y values are all different. When I compute...

...hat would turn off the information weighting of the box size (I have smaller randomized trials getting less weight than a much larger non-randomized trial). The function is forestplot() from rmeta. Thanks for any help. Gerard Slightly modified working function with data and a call follows: fplot=function (labeltext, mean, lower, upper, align = NULL, is.summary = FALSE, clip = c(-Inf, Inf), xlab = "", zero = 1, graphwidth = unit(3,"inches"), col = meta.colors(), xlog = FALSE, xticks = NULL, xlow=0, xhigh, digitsize, ...) { require("grid&quo...

...(hansen_tdum[,10]) EX1 <- as.matrix(hansen_tdum[,19]) y <- EX1 x <- ??????????????? for (fmp in 1:1){ cat ("Tax and Spend, Linear ","\n") cat ("\n") whiten <- 1 kernel <- 3 band <- 4 out <- fm(y,x,1,1) cat ("\n") cat ("\n") if (fplot == 1){ mtit <- "Ependiture, 1986:2011" xtit <- "Figure 1" ytit <- "F stat" t <- nrow(y) firstob <- 1986 + round(.15*t)/4 inc <- .25 rf <- nrow(out$f) crit <- matrix(1,rf,1)%*%cbind(15.2,6.22,7.815) ytics <- range(cbind(out$f,crit)) xx <- a...