similar to: meaning of tests presented in anova(ols(...)) {Design package}

Greetings, I have a groupedData (nmGroupedData) object created with the following syntax: Soil <- groupedData( ksat ~ conc | soil_id/sar/rep, data=soil.data, labels=list(x='Solution Concentration', y='Saturated Hydraulic Conductivity'), units=list(x='(cmol_c)', y='(cm/s)') ) the original data represents longitudinal observations in the form of:

Dear R useRs, I have a problem with nls.lm function of minpackl.lm package. I need to fit the Van Genuchten Model to a set of data of Theta and hydraulic conductivity with nls.lm function of minpack.lm package. For the first fit, the parameter estimates keep changing even after 1000 iterations (Th) and I have a following error message for fit of hydraulic conductivity (k); Reason for

On 10/06/2017 14:42, Michael Felt wrote: > > Next chapter in packaging.(Not meant to be extensive, only what I run > across and is easy to report) c) 378 | int quota_root_default_init(struct quota_root *root, const char *args, 379 | const char **error_r) 380 | { 381 | const struct quota_param_parser default_params[] = {

Hi, I am using the lme package to fit mixed effects models to a set of data. I am having a difficult time understanding the *meaning* of the numDF (degrees of freedom in the numerator), denDF (DF in the denomenator), as well as the Intercept term in the output. For example: I have a groupedData object called 'Soil', and am fitting an lme model as follows: ## fit a simple model #

Dear all R users, I am really struggling to determine the most appropriate lag order of ARIMA model. My understanding is that, as for MA [q] model the auto correlation coeff vanishes after q lag, it says the MA order of a ARIMA model, and for a AR[p] model partial autocorrelation vanishes after p lags it helps to determine the AR lag. And most appropriate model choosed by this argument gives

#stdout to /dev/null to see only the error messages It comes down to more issues with how IBM xlc handles (less elegantly) Compound Literals compared to GCC. michael at x071:[/data/prj/aixtools/github/dovecot/x071-test]make -i >/dev/null "../../../../src/x071-test/src/plugins/quota/quota.c", line 382.17: 1506-196 (S) Initialization between types "char* const" and

Hej, i need the which() funktion to find the positions of an entry in a matrix. the entries i'm looking for are : seq(begin,end,0.01) and there are no empty spaces i'm searching in the right range. so i was looking for the results R can find and i recieved this answer. for (l in

Hey, all. I had a quick question about fitting new glm values and then looking at the error around them. I'm working with a glm using a Gamma distribution and a log link with two types of treatments. However, when I then look at the predicted values for each category, I find for the one that is close to 0, the error (using se.fit=T with predicted) actually makes it overlap 0.

Martin, Thanks for the helpful reply. Alas I had forgotten that (implied) unfavorable comparisons of *nix systems with Windows systems would likely draw irate (but always substantive) responses on the R-devel list -- poor phrasing on my part. :) Regardless, let me try to address some of the concerns related to the construction of the MRE itself and try to see if we can clean away the shrubbery

This is cross-posted from SO (https://stackoverflow.com/q/47079702/1414455), but I now feel that this needs someone from R-Devel to help understand why this is happening. We are facing a weird situation in our code when using R's [`runif`][1] and setting seed with `set.seed` with the `kind = NULL` option (which resolves, unless I am mistaken, to `kind = "default"`; the default being

I have used lme() on data from a between-within subjects experiment. The correct ANOVA table is known because this is a textbook example (Experimental Design by Roger Kirk Chapter 12: Split-Plot Factorial Design). The lme() F-values differ from the known results. Please help me understand why. d<-read.table("kirkspf2.dat",header=TRUE) for(j in 1:4) d[,j] <- factor(d[,j]) ### Make

Hello Folks, Very new to R so bear with me, running 5.2 on XP. Trying to do a zero-inflated negative binomial regression on placental scar data as dependent. Lactation, location, number of tick larvae present and mass of mouse are independents. Dataframe and attributes below: Location Lac Scars Lar Mass Lacfac 1 Tullychurry 0 0 15 13.87 0 2 Somerset 0 0 0

In the code below, you seem to be essentially using the random number generator to implement a hash function. This isn't a good idea. My impression is that pseudo-random number generation methods are generally evaluated by whether the sequence produced from any seed "appears" to be random. Informally, there may be some effort to make long sequences started with seeds 1, 2, 3, etc.

On 10/06/2017 17:23, Michael Felt wrote: > On 10/06/2017 14:42, Michael Felt wrote: >> >> Next chapter in packaging.(Not meant to be extensive, only what I run >> across and is easy to report) > > c) > > 378 | int quota_root_default_init(struct quota_root *root, const > char *args, > 379 | const char **error_r) >

We collected more data to address some of the questions from the reviewers. Note this time we use clang itself as the benchmark. We choose clang because we think it's a typical C++ program and the reviewers here have good knowledge of the code base. What we measure is running time for clang to compile a large preprocessed source file (4.98M lines of .ii file), using different compilation

On 10/06/2017 17:26, Michael Felt wrote: > On 10/06/2017 17:23, Michael Felt wrote: >> On 10/06/2017 14:42, Michael Felt wrote: >>> >>> Next chapter in packaging.(Not meant to be extensive, only what I >>> run across and is easy to report) So, now in an attempt to report on where I am at... michael at

Bill, I have clarified this on SO, and I will copy that clarification in here: "Sure, we tested them on other 8-digit numbers as well & we could not replicate. However, these are honest-to-goodness numbers generated by a non-adversarial system that has no conception of these numbers being used for anything other than a unique key for an entity -- these are not a specially constructed

Justin, Sean and other people interested in this proposal, I'm wondering if you have chances to read the new experiment results in my last email sent 2 weeks ago. Can you share you thoughts, or you have other tests that you want to to run? I'm in the final stage of preparing the patch. If you are OK, I can sent out the patch soon. Thanks, -Rong On Wed, Aug 19, 2015 at 5:18 PM, Philip

>>>>> Tirthankar Chakravarty <tirthankar.lists at gmail.com> >>>>> on Fri, 3 Nov 2017 13:19:12 +0530 writes: > This is cross-posted from SO > (https://stackoverflow.com/q/47079702/1414455), but I now > feel that this needs someone from R-Devel to help > understand why this is happening. Why R-devel -- R-help would have been

Hello, I'm a bit new to the world of R so forgive my ignorance. I'm trying to do a zero-inflated negative binomial regression and have received an error message and i'm not sure what it means. I'm running R 2.5.1 on XP. I have just tried a really simple version of the model to see if it would run before I put all the variables in. I have attached all the variables to the