similar to: Ooops, small mistake fixed (pretty printing multiple models)

A few days ago, I had asked this question. Consider this situation: > x1 <- runif(100); x2 <- runif(100); y <- 2 + 3*x1 - 4*x2 + rnorm(100) > m1 <- summary(lm(y ~ x1)) > m2 <- summary(lm(y ~ x2)) > m3 <- summary(lm(y ~ x1 + x2)) You have estimated 3 different "competing" models, and suppose you want to present the set of models in one table. xtable(m1) is

Consider this situation: > x1 <- runif(100); x2 <- runif(100); y <- 2 + 3*x1 - 4*x2 + rnorm(100) > m1 <- summary(lm(y ~ x1)) > m2 <- summary(lm(y ~ x2)) > m3 <- summary(lm(y ~ x1 + x2)) Now you have estimated 3 different "competing" models, and suppose you want to present the set of models in one table. xtable(m1) is cool, but doing that thrice would give

Hi there, I have been using the example provided bellow for a while, and It was working without any problem. Nevertheless, just since 2-3 days is not working, probably because I did update.packages(). I have tried to re-install the older versions of the packages Hmisc() and xtable(), but still does not work. Can you run this example, and tell me if you got the same problems? I use

I find Sweave very useful and I was trying to combine it with the latex package fancyvrb. I was trying to get line numbering and labels in order to reference the lines where particular commands occur. Unfortunately, I haven't been able to figure out how to do it. Maybe somebody can help me. The following is a sample Rnw file: the first part shows what I would like to get, the second what I

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

Hello everyone, Hope you all are doing great! I have been fitting arima models and performing forecasts pretty straightforwardly in R. However, I wanted to add a couple of regressors to the arima model to see if it could improve the accuracy of the forecasts but have had a hard time trying to do so. I used the following R function: arima(x, order = c(0, 0, 0), seasonal = list(order = c(0, 0,

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

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 ~ .

I am working on a script that takes numeric performance indicators and runs them against a series of regressors (dummy regressors, yes\no stuff via 0 and 1, e.g. Was is Christmas this week 0=no, 1=yes). The script is as follows (Written as a function): -- Begin Script -- doEnv <- function(HOUR,ENVNAME,REPORTNAME) { library(RODBC) library(forecast) library("geneplotter")

If I try the breakpoints() function (strucchange package) with a minimum segment size = the number of regressors, there appears the following error message: "minimum segment size must be greater than the number of regressors" According to the documentation: "breakpoints implements the algorithm described in Bai & Perron (2003) for simultaneous estimation of multiple

Here's an oops output on 2.4.5 + CVS/ext3. This happened while trying to do a mkinitrd (on RedHat 7.1). ksymoops 2.4.0 on i686 2.4.5-2smp. Options used -V (default) -k /proc/ksyms (default) -l /proc/modules (default) -o /lib/modules/2.4.5-2smp/ (default) -m /boot/System.map-2.4.5-2smp (specified) kernel BUG at inode.c:934! invalid operand: 0000 CPU: 1 EIP:

Sorry The problem was with my eyes, not with R, predict works as it is supposed to on a subset, I was misled by the labels, which looked like they were giving the wrong thing. Sorry again Peter

The model matrix for the code at the end the email is shown below. Since the model matrix doesn't have -1, I think that it is made of dummy regressors rather than deviation regressors. I'm wondering how to make a model matrix using deviation regressors. Could somebody let me know? > model.matrix(aaov) (Intercept) A2 B2 B3 A2:B2 A2:B3 1 1 0 0 0 0 0 2

I am working with the splm package. I use the spgm function: general estimation of a panel data model. Based on this approach, I know it is possible to compute a R2, eg the ratio of variation explained by a given model. My model is : bivmod<-spgm(logIKA~NBLITRE0+NBLITRE1,data=mydatap,listw=comsKnn.nbW,spatial.error=TRUE) I know that we can calculate the R^2 as the variance of the fitted

I am attempting to optimize a regression model's parameters to meet a specific target for the sum of positive errors over sum of the dependent variable (minErr below). I see two courses of action , 1) estimate a linear model then iteratively reduce the regressors to achieve the desired positive error threshold (naturally the regressors and predicted values are biased - but this is

How for the love of god can I prevent the lm() function from padding on to my factor variables? I start out with 2 tables: Table1 123123 124351 ... 626773 Table2 Count,IS_DEAD,IS_BURNING 1231,T,F 4521,F,T ... 3321,T,T Everything looks fine when I import the data. then we get a oh_crap <- lm(table1 ~ Count + IS_DEAD + IS_BURNING, table2) Magically when I look at my oh_crap coefficents

Dear all, I am implementing a redundant variables F-test. For that I need to compute 2 models, restricted and unrestricted, then extracting the residuals to calculate the test statistic. I borrowed this elegant solution from the LMtest package to rebuild the first of the matrices involved (the unrestricted one) on the basis of model spec. and data >red.var.test<-function(formula,

On Mon, 4 Apr 2016, varin sacha via R-help wrote: > Hi Deepak, > > In econometrics there is another test very often used : the white test. > The white test is based on the comparison of the estimated variances of > residuals when the model is estimated by OLS under the assumption of > homoscedasticity and when the model is estimated by OLS under the > assumption of

Hello, I've got a rather strange setup over here with about 6 ext3 partitions, one 50gig lvm partition and one 2 gig software-raid1 partition running under a heavily patched 2.4.10 kernel (various netfilter patches, freeswan, current lvm patch (1.0.1-rc4 and current ext3 patch). Furthermore I have all of those neccessary filesystem tools, so don't tell me to upgrade :-) The machine was

Don't know how that last email took off, but that wasn't suppose to happen. Any the root 3 59.6 0.0 0 0 ? R< 10:16 11:04 [events/0] is a kernel thread that handles weird irq stuff. I just disabled onboard sound and USB and it went away. I'm still left with my other problems though, here they are 2.) I'm having LMB and DMB problems on the server,