similar to: predict.ar() produces wrong SE's (PR#9614)

dear R users, I am pleased to announce that segmented 2.1-0 is now available on CRAN. segmented focuses on estimation of breakpoints/changepoints of segmented, i.e. piecewise linear, relationships in (generalized) linear models. Starting with version 2.0-0, it is also possible to model stepmented, i.e. piecewise constant, effects. In the last release both models may be fitted via a formula

dear R users, I am pleased to announce that segmented 2.1-0 is now available on CRAN. segmented focuses on estimation of breakpoints/changepoints of segmented, i.e. piecewise linear, relationships in (generalized) linear models. Starting with version 2.0-0, it is also possible to model stepmented, i.e. piecewise constant, effects. In the last release both models may be fitted via a formula

Hello, i am syncing 2 directorys with rsync. There is nothing to do (i didn't changed anything). Here is the output: building file list ... done wrote 371 bytes read 20 bytes 782.00 bytes/sec total size is 5062161 speedup is 12946.70 Why did rsync wrote 371 bytes?? This output says rsync didn't changed anything! regards, hampel

Hello, I'm seeking ideas on how to remove outliers from a non-normal distribution predictor variable. We wish to reset points deemed outliers to a truncated value that is less extreme. (I've seen many posts requesting outlier removal systems. It seems like most of the replies center around "why do you want to remove them", "you shouldn't remove them", "it

Hello, I'm learning about robust M-estimators right now and had settled on the "Huber Proposal 2" as implemented in MASS, but further reading made clear, that at least 2 further weighting functions (Hampel, Tukey bisquare) exist. In a post from B.D. Ripley going back to 1999 I found the following quote: >> 2) Would huber() give me results that are similar (i.e., close

Dear All, When I run rlm to obtain robust standard errors, my output does not include p-values. Is there any reason p-values should not be used in this case? Is there an argument I could use in rlm so that the output does include p-values? Thanks in advance, Celso [[alternative HTML version deleted]]

Dear R-users, I have two outliers related questions. I. I have a vector consisting of 69 values. mean = 0.00086 SD = 0.02152 The shape of EDA graphics (boxplots, density plots) is heavily distorted due to outliers. How to define the interval for outliers exception? Is <2SD - mean + 2SD> interval a correct approach? Or should I define 95% (or 99%) limit of agreement for data interval,

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of

hi guys and gals ... How are you all ... i have to do something in robust regression by R programm , and i have some problems as following: *the first :* suppose w(r) =1/(1 r^2) and r <- c(7.01,2.07,7.061,5.607,8.502,54.909,12.222) and i want to exclude some values from r so that (abs(r)>4.9 )... after ,i want to used (w) to get on coefficients beta0 and beta1 (B1 <-

Hi All, I would like to use meta.summaries from package rmeta to do a meta-analysis. I have available effect sizes as r's (which could be easily transformed to effect sizes in terms of d's). My problem is that I'm not sure what the se's of these r's should be ... The r-values are themselves computed from F-tests and t-tests for various studies. Are there R-functions that

dear R wizards: apologies for two queries in one day. I have a long form data set, which identifies about 5,000 regressions, each with about 1,000 observations. unit date y x 1 20060101 <two values> 1 20060102 <two values> ... 5000 20081230 <two values> 5000 20081231 <two values> I need to run such regressions many many times, because they are part of an

Hello, Can anyone explain why the following message appears for the function model.tables, where se=T? In the V&R MASS text, p.285 the se=T option works for a split plot example that seems similar to my operation. But the model.tables documentation, in the Arguments section for "se", states "should standard errors be computed?". "Warning: Warning in

I?m entirely stumped on this particular issue and really hoping someone has some advice for me. I am running a covariant model in lm I would like to give the standard errors or the confidence intervals for the fitted lines. I?ve been using the dataset OrangeSprays where I want lines for each level of treatment over the covariant ?colpos?. I?ve been able to calculate intercepts and slopes for

dear members, I have a function ygrpc which acts on the daily price increments of a stock. It returns the following values: ygrpc(PFC.NS,"h") [1] 2.149997 1.875000 0.750000 0.349991 2.100006 0.199997 4.000000 2.574996 0.500000 0.349999 1.500000 0.700001 [13] 0.500000 1.300003 0.449997 2.800003 2.724998 66.150002 0.550003 0.050003 1.224991 4.899994 1.375000

Hi I have an output data Data.csv this style: ,"V1","V2","V3" 1,"-9552","9552","C" 2,"0","9653","0" 3,"9614","9614","V" 4,"0","9527","0" 5,"-9752","9752","C" 6,"0","9883","0"

I just updated rpart to the latest version (3.1.0). There are a number of changes between this and previous versions, and some of the code I've been using with earlier versions (e.g. 3.0.2) no longer work. Here is a simple illustration of a problem I'm having with xpred.rpart. iris.test.rpart<-rpart(iris$Species~., data=iris[,1:4], parms=list(prior=c(0.5,0.25, 0.25))) + ) >

Greetings, Sorry, the last message was sent by mistake! Here it is again: I encounter a strange problem computing some numerical integrals on [0,oo). Define $$ M_j(x)=exp(-jax) $$ where $a=0.08$. We want to compute the $L^2([0,\infty))$-inner products $$ A_{ij}:=(M_i,M_j)=\int_0^\infty M_i(x)M_j(x)dx $$ Analytically we have $$ A_{ij}=1/(a(i+j)). $$ In the code below we compute the matrix

I have followed all the install note for A2billing and have everything installed and configured and my asterisk works except the callingcard application. Added the following [callingcard] ; CallingCard application exten => 777,1,Answer exten => 777,2,Wait,2 exten => 777,3,DeadAGI,a2billing.php exten => 777,4,Wait,2 exten => 777,5,Hangup I am using 777 as the calling card

Hi Akshay, (Please include r-help when replying) You have learned that PFC.NS and snl[[159]] are not identical. Now you have to figure out why they differ. This could also point to a bug or a logic error in your program. Figuring out how two objects differ can be a bit tricky, but with experience it becomes easier. (Some others may even have some suggestions for good ways to do it.) Basically