similar to: Problem with predict() and factors

to clean up some code I would like to make a list of arbitrary length to store?various objects for use in a loop sample code: ############ BEGIN SAMPLE ############## # You can see the need for a loop already linearModel1=lm(modelSource ~ .,mcReg) linearModel2=step(linearModel1) linearModel3=lm(modelSource ~ .-1,mcReg) linearModel4=step(linearModel3) #custom linearModel5=lm(modelSource ~ .

Why are my coefficients getting appended with a 1? It borks a match I do later against the original list that doesn't have the random 1 added to the end. > linearModel[[1]] Call: lm(formula = modelSource ~ +UNITBUILD + UNITDB + ITBUILD + ITDB + UATBUILD + UATDB + HOGANCODE + RCF + ReleaseST1 + ReleaseST2 + ReleaseBLA + Small.Bank.Acquisitions + HLY.NewYear + HLY.MLK + HLY.PRES +

I did have a verbose description of why but rather then make everyone's eyes bleed with useless details I ask the following :) To make a long story short: How can I make newmcReg[[i]]["PreIO308"] go away in the following list... er vector... no wait array.... dataframe.... awww crap... summary(newmcReg[[i]]) UNITBUILD UNITDB ITBUILD ITDB Mode :logical

I am having trouble plotting outliers on time series. Give then following code: ############################################################ # find STL Outliers by weight and append sh2, use Robust # this should allow the initial outliers to be filtered # this section may be commented out. ############################################################ tsSourceDiag <-

Hallo all I realise this might be a "too much to ask" question, but can I improve the Lattice plot produced by the following code? The type of figure I would like to produce in each segment of the plot appears below the code. library(reserving) # http://toolkit.pbwiki.com/RToolkit <http://toolkit.pbwiki.com/RToolkit> data(GenIns) GenInsInc <- incrementalTriangle(GenIns)

I imported a spreadsheet into a variable sh e.g. sh$aaaa, sh$bbbb, etc... doing the following: tsSource <- ts(paste("sh$",NAMEVARIABLE,sep="") ... ) fails. The paste isn't evaluating properly. What is the proper way to concatenate a data source with a member name such that they evaluate properly. actual code below: doEnv <-

##### BEGIN CODE ###### #!/usr/bin/perl ###### # # --start, -s = The date you would like to start generating regressors #--end, -e = When to stop generating holiday regressros # --scope, -c = D, W for Daily or Weekly respectively (e.g. Does this week have a particular holiday) # --file, -f = Ummm where to write the output silly! # # **NOTE** The EOM holiday is "End of Month" for

Here is the correct version. The old version is the redirect only version of the script. ### BEGIN SCRIPT #### #!/usr/bin/perl ###### # --start, -s = The date you would like to start generating regressors #--end, -e = When to stop generating holiday regressros # --scope, -c = D, W for Daily or Weekly respectively (e.g. Does this week have a particular holiday) # --file, -f = Ummm where to write

Hello, With this program I try to repeat analysis for different years. The results of the analysis are not printed when in the loop, except for the year sequence. What is wrong? Thanks a lot. for (i in 92:99){ cat("\n", "=============================================================\n", "YEAR =",i,"\n",

Hello R-folks, I don't get the color of the legend in a lattice-plot right. I select a palette from RColorBrewer and use (with a col = mypalette argument) it in the barchart plot. The resulting graph shows the new palette in the graph, but uses the standard palette in the legend rectangles. Adding a col argument into auto.key uses the new palette with the legend text, but not in the

I am reading regressors from an excel file (I have no control over the file) and some of the element names have spaces: i.e. "Small Bank Aquired" but I have found that lm(SourceData ~ . - "Small Bank Aquired", mcReg) doesn't work (mcReg = modelCurrentRegressors) As they are toggles I have ran them through factor() to be treated propertly as 0 or 1 but due to the fact I

I would like to ask for advice from R experts about the benefits or dangers of using attr to return information with an object that is returned from a function. I have a feeling as though I have cheated by using attributes, and wonder if I've done something fishy. Maybe I mean to ask, where is the dividing line between attributes and instance variables? The separation is not clear in my mind

Hello R-folks, I don't get the color of the legend in a lattice-plot right. I select a palette from RColorBrewer and use it in the barchart plot. The resulting graph shows the new palette in the graph, but in the legend rectangles the standard palette is used. Adding a col argument into auto.key uses the new palette with the legend text, but not in the rectangle fill. What am I missing?

I have a weekly data set imported via: tsSource=ts(sh1$I000,start=c(2004,1),freq=52) I am now getting to some 'spit and polish' but I realize something I can't wrap my head around. Given an outlier I find at say tsSource[54] ... how can get translate index 54 into the date\week. I mean I can figure out obviously that entry 52 is last week of 2004 but since the data goes for many

I'm using ssplot for drawing a map of Austria and colour the nine provinces regarding their share of employment. Now I wanted to add the figures in each province and failed miserably. Using the locator() and text() function caused the error message "invalid graphics state". I try to show you what I have done below, maybe you can find a general fault in my codes. I know that it's

Dear List, Consider the following example x=c(1,2,3,4,5) y=c(2,4,6,8,10) linearmodel=lm(y~x) To predict a y-value if you know the corresponding x value is very easy with the command predict. predict(linearmodel, newdata=(x=1.5)) The other way around, to predict an x-value with a corresponding y-value, doesn't work unfortunately. Is there another function that can do that, or do I need to

Dear list members, I've uploaded a new version of the Rcmdr package to CRAN. There are many additions and (I hope) improvements, as indicated in the relevant portion of the CHANGES file, reproduced below. As usual, comments, suggestions, and bug reports are appreciated. John ------------------------------------------- Version 0.8-4 o Minor bug fixes and additional input-error

Dear list users, I modeled the probability of occurrence of one species: "Cyperus dilatatus". I modeled the species using three different approaches: c("random","target","index") What I want to achieve is to make a plot of all prediction maps in a row with to conditional variables, that is, with the species and the approach I prepared a data.frame to try

Hello everyone, I am trying to do within subjects repeated measures anova followed by the test of sphericity (sample dataset below). I am able to get either mixed model or linear model anova and TukeyHSD, but have no luck with Repeated-Measures Assuming Sphericity or Separate Sphericity Tests. I am trying to follow example from "car" package, but it seems that I am not getting something

To make a long story short I was doing some in-sample testing in which some dynamically created regressors would end up either all true or all false based on the validation portion. In my case a new mainframe configuration (this is a crappy way to handle a level shift but I do what I can.) So here is the code snippet that finally let me pre-check my regressors and drop any of them that were all