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I found it easy to use R when typing data manually into it. Now I need to read data from a file, and I get the following errors: > refdata = > read.table("K:\\MerchantData\\RiskModel\\refund_distribution.csv", header > = TRUE) Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, : line 1 did not have 42 elements > refdata = > read.table("K:\\MerchantData\\RiskModel\\refund_distribution.csv") Error in scan(file, what, nmax, sep,...

Here is my little scriptlet: optdata = read.csv("K:\\MerchantData\\RiskModel\\AutomatedRiskModel\\soptions.dat", header = FALSE, na.strings="") attach(optdata) library(MASS) setwd("K:\\MerchantData\\RiskModel\\AutomatedRiskModel") for (i in 1:length(V4) ) { x = read.csv(as.character(V4[[i]]), header = FALSE, na.strings=""); y = x[,1...

Here is what I tried: optdata = read.csv("K:\\MerchantData\\RiskModel\\AutomatedRiskModel\\soptions.dat", header = FALSE, na.strings="") optdata attach(optdata) for (i in 1:length(V4) ) { x = read.csv(V4[[i]], header = FALSE, na.strings="");x } And here is the outcome (just a few of the 60 records successfully read): > optdata = > rea...

I'm trying to use the survey package to calculate a risk difference with confidence interval for binge drinking between sexes. Variables are X_RFBING2 (Yes, No) and SEX. Both are factors. I can get the group prevalences easily enough with result <- svyby(~X_RFBING2, ~SEX, la04.svy, svymean, na.rm = TRUE) and then extract components from the svyby object with SE() and coef() to do the

I have a number of files containing anywhere from a few dozen to a few thousand integers, one per record. The statement "refdata18 = read.csv("K:\\MerchantData\\RiskModel\\Capture.Week.18.csv", header = TRUE,na.strings="")" works fine, and if I type refdata18, I get the integers displayed, one value per record (along with a record number). However, when I try " fitdistr(refdata18,"negative binomial")", or hist.scott(refdata18...

...plot, title = title, description = description) Model: Student-t Distribution Estimated Parameter(s): alpha beta gamma delta 1.5340000 0.2750000 0.3211991 -0.9922306 Description: Tue Sep 23 22:18:44 2008 by user: Ted > refdata18 = read.csv("C:\\MerchantData\\RiskModel\\Capture.Week.18.csv", > na.strings="") > stableFit(refdata18[,1],alpha = 1.75, beta = 0, gamma = 1, delta = 0, + type = c("q", "mle"), doplot = TRUE, trace = FALSE, title = NULL, + description = NULL) Title: Stable Parameter Estimation Call:...

...") > rs <- dbSendQuery(con, "select * from merchants") > df <- fetch(rs, n = 150) > df And of course, that last statement is followed by the entire contents of "merchants" Now, I have a script like the following: refdata18 = read.csv("K:\\MerchantData\\RiskModel\\ndays18.csv", na.strings="") x1 = refdata18[,1] library(MASS) ex1 = fitdistr(x1,"exponential") str(ex1) Now, the contents of ndaysXX.csv represent records where one of the date values is in week XX of the current year. We don't yet have data spanning multiple years,...

...umbers? To: r-help@r-project.org Message-ID: <19600308.post@talk.nabble.com> Content-Type: text/plain; charset=us-ascii I have a number of files containing anywhere from a few dozen to a few thousand integers, one per record. The statement "refdata18 = read.csv("K:\\MerchantData\\RiskModel\\Capture.Week.18.csv", header = TRUE,na.strings="")" works fine, and if I type refdata18, I get the integers displayed, one value per record (along with a record number). However, when I try " fitdistr(refdata18,"negative binomial")", or hist.scott(refdata18...