mike-lawrence

library(CircStats)

#define a data generator for the uvm model
get_mix_data = function( n , rho , kappa , seed ){
	set.seed(seed)
	to_return = rep(NA,n)
	trial_is_vm = as.logical(rbinom(n,1,rho))
	to_return[trial_is_vm] = rvm(sum(trial_is_vm),pi,kappa)
	to_return[!trial_is_vm] = runif(sum(!trial_is_vm),0,2*pi)
	to_return = to_return-pi #center the data on 0

mike-lawrence

ezANOVA <-
function(
	data
	, dv
	, wid
	, within = NULL
	, between = NULL
	, observed = NULL
	, diff = NULL
	, reverse_diff = FALSE

mike-lawrence

#A function to obtain predictions from a fitted lmer object. 
#If to_predict is null, the function will attempt to build a 
#design matrix for prediction from the information in the fit 
#itself. If a .() object is passed to as to_predict, variables 
#listed in to_return are used to create the design matrix. A
#data frame may also be passed as to_predict.

ezPredict <-
function(
	fit

mike-lawrence

extrema_c = function (y, ndata = length(y), ndatam1 = ndata - 1){
	minindex <- maxindex <- NULL
	nextreme <- 0
	cross <- NULL
	ncross <- 0
	z1 <- sign(diff(y))
	index1 <- seq(1, ndatam1)[z1 != 0]
	z1 <- z1[z1 != 0]
	if(!(is.null(index1) || all(z1 == 1) || all(z1 == -1))){

mike-lawrence

#define two useful helper functions
colMean = function(x){
	dimx = dim(x)
	.Internal(colMeans(x,dimx[1],dimx[2],na.rm=TRUE))
}
colVar = function(x){
	dimx = dim(x)
	x.mean = .Internal(colMeans(x,dimx[1],dimx[2],na.rm=TRUE))
	err = t(t(x)-x.mean)
	err.sq = err*err

mike-lawrence

library(ez)
data(ANT)

########
#this will work
########
rt = ezMixed(
	data = ANT[ANT$error==0,]
	, dv = .(rt)
	, random = .(subnum)

mike-lawrence

library(plyr)
a = read.table('temp.txt')
names(a) = c('trial','event','time')

a$row = as.numeric(row.names(a))
a$event = factor(a$event,levels=c('collect_data','A','B','C','write_data'))

b = ddply(
	.data = a
	, .variables = .(trial,event)

mike-lawrence

fptcdf = function(z,x0max,chi,driftrate,sddrift) {
    zs = z*sddrift
    zu = z*driftrate
    chiminuszu = chi-zu
    xx = chiminuszu-x0max
    chizu = chiminuszu/zs
    chizumax = xx/zs
    tmp1 = zs*(dnorm(chizumax)-dnorm(chizu))

mike-lawrence

$ sudo ./configure --with-x=no --enable-R-shlib
checking build system type... x86_64-unknown-linux-gnu
checking host system type... x86_64-unknown-linux-gnu
loading site script './config.site'
loading build-specific script './config.site'
checking for pwd... /bin/pwd
checking whether builddir is srcdir... yes
checking for working aclocal... missing
checking for working autoconf... missing
checking for working automake... missing

mike-lawrence

#Load the CicStats package
library(CircStats)

#Define a customization of circ.mean{CircStats} that permits weighting observations
circ.weighted.mean = function (x,rho){
	sinr = sum(rho*sin(x))
	cosr = sum(rho*cos(x))
	circmean = atan2(sinr, cosr)
	return(circmean)
}