similar to: lm ~ v1 + log(v1) + ... improve adj Rsq ¿any sense?

Hi to all I tried help.search("rsq") and found Help files with alias or concept or title matching 'rsq.rpart' using regular expression matching: rsq.rpart(rpart) Plots the Approximate R-Square for the Different Splits then I tried to use the function but I got the error object not found must I load any package before? there is nothing in the

Signed-off-by: Ilia Mirkin <imirkin at alum.mit.edu> --- Not sure how many steps are needed for the necessary accuracy. Just doing 2 because that seems like a reasonable number. .../nouveau/codegen/nv50_ir_lowering_nvc0.cpp | 42 ++++++++++++++++++++-- 1 file changed, 39 insertions(+), 3 deletions(-) diff --git a/src/gallium/drivers/nouveau/codegen/nv50_ir_lowering_nvc0.cpp

Oh right. I think the NVIDIA blob executes those steps conditionally based on the upper bits not being 0x7ff (== infinity/nan). I should do the same thing here. [FWIW I was able to test the nv50 code last night and that one's a total fail for rcp/rsq... will need to port that over to my nvc0 and debug there.] On Mon, Feb 23, 2015 at 8:24 AM, Roland Scheidegger <sroland at vmware.com>

Does this give correct results for special floats (0, infs)? We tried to improve (for single floats) x86 rcp in llvmpipe with newton-raphson, but unfortunately not being able to give correct results for these two cases (without even more additional code) meant it got all disabled in the end (you can still see that code in the driver) since the problems are at least as bad as those due to bad

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

Dear Adrian and Ian (and r-helpers), I encountered a curious result in developing an example using the bicreg function in the BMA package: I noticed that pairs of models with equal R^2 and equal numbers of predictors had nevertheless different BIC values. Looking at the bicreg function, the definition of BIC appears to be the usual one, or close to it [bic <- n * log(1 - r2/100) + (size - 1) *

Problem: I am sorting through model selection process for first time and want to make sure that I have used glm, stepAIC, and update correctly. Something is strange because I get a different result between: 1) a glm of 12 predictor variables followed by a stepAIC where all interactions are considered and then an update to remove one specific interaction. vs. 2) entering all the terms

Dear useRs, I am trying to model a time series with a transfer function. I think it can be put into the ARMA framework, and estimated with the 'arima' function (and others have made similar comments on this list). I have tried to do that, but the results have so far been disappointing. Maybe I am trying to make 'arima' do something it can't... The data are time series of

rlnorm takes two 'shaping' parameters: meanlog and sdlog. meanlog would appear from the documentation to be the log of the mean. eg if the desired mean is 1 then meanlog=0. So to generate random values that fit a lognormal distribution I would do this: rlnorm(N , meanlog = log(mean) , sdlog = log(sd)) But when I check the mean I don't get it when sdlog>0. Interestingly I

I have two variables which show a typical quantile relation I would like to fit quantile regression models based on both logarithm and polynomial of second order functions within quantreg. Any help appreciated... Cheers Duccio Herewith the values: ------ var1 var2 0.96429 0.00138 1 0.02316 1.03145 0.09323 1.24088 0.77128 1.39869 0.86732 1.33728 0.63674 1.48299 0.96194

I've searched the Web with Google and do not find what might cause this particular error from an invocation of cenboxplot: cenboxplot(cu.t$quant, cu.t$ceneq1, cu.t$era, range=1.5, main='Total Recoverable Copper', ylab='Concentration (mg/L)', xlab='Time Period') Error in if (n > 0) (1L:n - a)/(n + 1 - 2 * a) else numeric() : argument is of length zero I do

All, I need to run this by everyone and see if someone has any idea's. I have a asterisk server setup and currently am receiving the inbound calling number where the name should be. My setup is.... One pri terminating into a Cisco 2431 router Sip messages from the Cisco get sent to a asterisk server linksys ata's a each remote end. I can receive the calling name if the call originates

Hello All: I am trying to replicate the results of an example found in Alan Agresti's "Categorical Data Analysis" on pages 267-269. The example is one of a 2 x 2 cross-classification table of ordinal counts: job satisfaction and income. I am able to get Agresti's results for the independence model (G^2 = 12.03 with df = 9) assuming as he does that the data is nominal, but

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934

Howdy! I've been doing a lot of troubleshooting, and haven't arrived at a solution yet. Kernel log attached. VBIOS also attached. Ubuntu 19.10 $ uname -a Linux joyful 5.3.0-26-generic #28-Ubuntu SMP Wed Dec 18 05:37:46 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux $ dpkg -l|grep nouveau ii libdrm-nouveau2:amd64 2.4.99-1ubuntu1 amd64