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2011 Oct 07
1
R equivalent of proc varclus
Dear List
What is the R package equivalent of Proc Varclus or Information Value. ANy
assistance in determining R equivalents of f Oblique Component Analysis
(PROC VARCLUS), Information Value
(IV) and Weight Of Evidence (WOE) analysis, and business intelligence
http://www.nesug.org/proceedings/nesug06/an/da23.pdf
Regards,
Ajay
Websites-
http://decisionstats.com
[[alternative HTML version
2005 Jul 09
1
aregImpute: beginner's question
...#Question for R-Help on aregImpute
########################################
#DOWNLOAD DATA (61Kb)
download.file("http://www.people.fas.harvard.edu/~corr/tc.csv","C:/R")
tc <- read.csv("tc.csv", header = TRUE)
d <- as.data.frame(tc)
n <- naclus(d)
plot(n); naplot(n) # Show patterns of NAs
#RUN aregImpute
set.seed(5)
f <- aregImpute(~y +
podb2+propdemocracy+avetrade1984dollars+concentration+cycle+polarity+propmid+terrgainer+
demgainer+ fedgainer+ popdengainer+ urbpopgainer+ tradeopgainer+
gdppcgainer+ terrloser+ demloser+ fedloser+ popdenloser+ urbpopl...
2007 May 31
0
Using MIcombine for coxph fits
...<- lapply(d[,c(4,5,7)], FUN=as.factor)
str(d)
summary(d)
---------------
Second, since there is missing data for several (but not all) of the
variables, investigate the patterns.
---------------
library(Hmisc)
na.pattern(d)
clus <- naclus(d, method='complete')
par(mfrow=c(2,2))
naplot(clus, which='all')
print(clus)
detach(package: Hmisc)
---------------
After examining the missing data patterns, impute 10 datasets using the
amelia function from the Amelia package. Check the densities of the
continuous variables to make sure they make sense.
---------------
library(Ame...
2004 Nov 23
5
number of pairwise present data in matrix with missings
is there a smart way of determining the number of pairwise present data
in a data matrix with missings (maybe as a by-product of some
statistical function?)
so far, i used several loops like:
for (column1 in 1:99) {
for (column2 in 2:100) {
for (row in 1:500) {
if (!is.na(matrix[row,column1]) & !is.na(matrix[row,column2])) {
pairs[col1,col2] <- pairs[col1,col2]+1