similar to: Interpreting NB GLM output - effect sizes?

Dear all R-users, I wanted to fit a Garch(1,1) model to a dataset by: >garch1 = garch(na.omit(dat)) But I got a warning message while executing, which is: >Warning message: >NaNs produced in: sqrt(pred$e) The garch parameters that I got are: > garch1 Call: garch(x = na.omit(dat)) Coefficient(s): a0 a1 b1 1.212e-04 1.001e+00 1.111e-14 Can any one

Hi, after upgrading to Asterisk 1.2.8 from 1.2.7.1 I got a problem with Grandstream BT100 after making an attended transfer (FLASH + NUMBER + SEND + WAIT ANSWER + TRANSFER). After the transfer, the display clears all the info except the clock, there is no dial tone, the WEB admin stops working. Incoming calls make the display light turn on but there is no ring and no callerid on the

Dear R-users, I have a basic question about how to determine the antilog of a variable. Say I have some number, x, which is a factor of 2 such that x = 2^y. I want to figure out what y is, i.e. I am looking for the antilog base 2 of x. I have found log2 in the Reference Manual. But I am struggling how to get the antilog of that. Any help will be appreciated! > version platform

I would like to know if it is possible to perform negative binomial regression with rate data (incidence density) using the glm.nb (in MASS) function. I used the poisson regression glm call to assess the count of injuries across census tracts. The glm request was adjusted to handle the data as rates using the offset parameter since the population of census tracts can vary by a factor of

Hi, I am using R for microarray data anlaysis. When I normalize my data, it converts all my data in to log base 2 values. how can I convert back to log base 10..is there any function in R which I can use or how can I take anti log. or is there any function in R for antilog. Please let me know,..if anyone knows.. Thank you so much, Saurin ===== Saurin's WebWorld:

Hello, in the data.frame "resultsfuzzy" I would like to replace the characters in the second column ("5a", "5b", ... "5e") with numbers from 1 to 5. The data.frame has 39150 entries. I seems to work on samples that are << nrow(resultsfuzzy) but it takes suspicously long. Do you have any suggestions how to make the character replacing more

The following output results from fitting models using lmer and lm to data arising from a split-plot experiment (#320 from "Small Data Sets" by Hand et al. 1994). The data is given at the bottom of this message. My question is why is the sum of squares for variety (V) different in the ANOVA table generated from the lmer model fit from that generated by the lm model fit. The

Suppose we have the following data set: Men Women Dieting 10 30 Non-dieting 5 60 If I run the Fisher exact test in R then what does alternative = greater (or less) imply? For example: mat = matrix(c(10,5,30,60), 2,2) fisher.test(mat,alternative ="greater") I get the p-value = 0.01588 and odds ratio = 3.943534. Also, when I flip the rows of

Hi, make check fails in the way shown below when I try to build R-2.6.2 on OpenSuSE Factory x86_64. It builds fine on i586. (and on all older Versions of Opensuse) Is there something I can do? Are there known problems with some gcc versions? (Factory uses 4.3.0) Output from ./configure is ------------------------------------------------------------- R is now configured for

Hi folks, I'm trying to estimate bias-corrected percentile (BCP) confidence intervals on a vector from a simple for loop used for resampling. I am attempting to follow steps in Manly, B. 1998. Randomization, bootstrap and monte carlo methods in biology. 2nd edition., p. 48. PDF of the approach/steps should be available here: https://wyocoopunit.box.com/s/9vm4vgmbx5h7um809bvg6u7wr392v6i9 If

Dear R-help, I'm applying the surrogate Poisson glm, by following Venables & Ripley (7.3 pp238-42). >overall_cbind(expand.grid(treatment=c("Pema","control"),age=c("young","adult","old"),repair=c("excellent","good","poor")),Fr=c(8,0,7,1,2,0,2,7,1,4,7,1, 0,3,2,5,1,9))

Okay, I deleted most of this thread, so I was waiting for another message to respond to, so unfortunately this will be out of place in the thread. This is in response to Miroslav's idea about variable block sizes. I may be a bit out of my league here as I'm just starting to look at how the actual encoding gets done. But it seems to me that you could make a decent guess about when

I use by() to generate a summary statistics like so: Lbys <- by(dat[Nidx], dat$LipTest, summary) where Nidx is an index vector with names picking out the columns in the data frame dat. This returns a list of character arrays (see below for str() output) where the columns are named correctly but the rownames are empty strings and the values are strings prepended with the summary

Dear all, I hope to be the clearest I can. Let's say I have a dataset with 10 variables, where 4 of them represent for me a certain phenomenon that I call Y. The other 6 represent for me another phenomenon that I call X. Each one of those variables (10) contains 37 units. Those units are just the respondents of my analysis (a survey). Since all the questions are based on a Likert scale, they

Hi, This might be me missing something painfully obvious but why does the cube root of the following produce an NaN? > (-4)^(1/3) [1] NaN > As we can see: > (-1.587401)^3 [1] -4 Thanks! Greg

On Thu, Oct 17, 2002 at 09:51:02AM -0500, Brady Patterson wrote: > > Okay, I deleted most of this thread, so I was waiting for another message to > respond to, so unfortunately this will be out of place in the thread. > > This is in response to Miroslav's idea about variable block sizes. I may be a > bit out of my league here as I'm just starting to look at how the

Hi, I have some code I run interactively through the R interpreter and it works fine. I then run it as a script with Rscript and I get an error. The error is coming when Rscript builds a model matrix. Here is the Rscript code : #!/usr/lib/R/bin/Rscript --verbose require(MASS) options(contrasts = c("contr.treatment", "contr.poly")) .... form <- as.formula(paste(ef.var,

Hello, I am using the clogit (conditional logistic regression) on a simple data set which is not related to survivorship, which I understand to be fine. I have trouble understanding the output. I would like to find parameter estimates of the logistic models I am constructing with R, and am unclear as to what the coefficients represent that are provided. The below is a copy of my output.

Hello - I am trying to figure out R's transformation for interaction terms in a linear regression. My simple background understanding is that interaction terms are generally calculated by multiplying the centred (0-mean) variables with each other and then doing the regression. However, in this regard I would have expected to see the same p-value when I calculate summary(lm(Y~A:B)) for A:B

Dear all, quite a naive question: I have a data frame and I computed "the kernel density estimate" with density on each column. Now I'd like to export in a txt file the density function output for each column, but, when if I use write.table, I get a message "Error in as.data.frame.default(x[[i]], optional = TRUE) : can't coerce class "density" into a