search for: tvals

Hello, I want to have a title that will look something like: "Results for \theta=2.1", given that I have a variable theta=2.1, and \theta should show on the screen like the greek letter. I've tried a lot of things: theta <- 2.1 plot(1:10, main=expression(paste("Results for", theta, "=", eval(theta)))) or using bquote plot(1:10, main=paste("Results for

--Multipart_Mon_Nov_24_14:51:09_1997-1 Content-Type: text/plain; charset=US-ASCII >>>>> "PaulG" == Paul Gilbert <pgilbert@bank-banque-canada.ca> writes: MM> The code is basically in V&R 1 and 2; V&R2 on p.167. I have it as a MM> C function that I used to dyn.load into S-plus in order MM> to prove that S-plus was using it.

If you found my subject heading to be confusing then I'm sure you'll enjoy the example I've included below. I find the apply type functions to be wonderful for avoiding loops but when I use them with existing functions, I end up using loops anyway to extract the vectors I want. I would appreciate it if someone could show me how to avoid these loops. Thanks. EXAMPLE:

Hello everyone, I'm trying to estimate the parameters of the returns series attached using the GARCH code below, but I get the following error message: Error in solve.default(Hessian) : system is computationally singular: reciprocal condition number = 0 Error in diag(solve(Hessian)) : error in evaluating the argument 'x' in selecting a method for function 'diag' Can

Full_Name: Juan Gea Version: R version 2.6.2 OS: Fedora Core 6 Submission from: (NULL) (79.153.48.49) Abort: objeS <- matrix("AAA",1000000) class(objeS) outTxt <- textConnection("vaClob", open = "w", local = FALSE) dput(objeS,outTxt) close(outTxt) R version 2.6.2 (2008-02-08) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN

Curious to know if this warning is expected behavior, and if so, what is the recommended way instead: > dput(letters, file = stderr()) c("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p",

Hello all, I'm trying to create a heatmap using 2 matrices I have: z and v. Both matrices represent different correlations for the same independent variables. The problem I have is that I wish to have the values from matrix z to be represented by color intensity while having the values from matrix v to be represented by circle size. I currently have the following in front of me and an unsure

I am attempting to lower the selectCC instruction to the instruction set of the backend I'm working on and I cannot seem to find a way to correctly implement this instruction. I know how this instruction should get implemented; I just have yet to find a way to do it. I want the select_cc instruction to be lowered into a comparison followed by a conditional move. I've attempted to use a

I am working with some survival data with missing values. I am using the mice package to do multiple imputation. I have found code in this thread which handles pooling of the MI results: https://stat.ethz.ch/pipermail/r-help/2007-May/132180.html Now I would like to plot a survival curve using the pooled results. Here is a reproducible example: require(survival) require(mice) set.seed(2) dt

I define the following function to convert a t-value with degrees of freedom DF to another t-value with different degrees of freedom fullDF: tConvert <- function(tval, DF, fullDF) ifelse(DF>=1, qt(pt(tval, DF), fullDF), 0) It works as expected with the following case: > tConvert(c(2,3), c(10,12), 12) [1] 1.961905 3.000000 However, it gives me warning for the example below although the

There's a little source code (typo?) bug in "samba-2.0.4/source/lib/system.c" that hurts compilation at least on HPUX 9.0x (with HP's cc, not gcc!) !! In HPUX's "/usr/include/sys/time.h": .. # ifndef _STRUCT_TIMEVAL # define _STRUCT_TIMEVAL /* Structure returned by gettimeofday(2) system call and others */ struct timeval { unsigned long tv_sec;

Dear R users, I came up with some simple functions to give me the standard betas and tolerance values from a predefined lm() model. I have been trying to insert the results from these functions into the coefficients matrix in a modified summary.lm function that I'm calling summary2 (I'd never edit the summary.lm function directly!!). I managed to get the results inserted into the

I really can't figure out how to get and set array indices from the c interface. so to get an element I'm calling tindex = *fn\SymbolTable(*index\name) index = LLVMBuildLoad(builder,tindex,"index") arr = *fn\SymbolTable(*array\name) arrptr = LLVMBuildLoad(Builder,arr,"arrayptr") tmp = LLVMBuildGEP(Builder,arrptr,index,0,"ptr") ptr =

I have tried the following code to plot and save many box plots in files. The code works by itself, but does not run in a loop. The error indicates that there is no device. The error is printed below the code. Code: for(i in 1:len) { A = as.numeric(delta[Delta[i,1]]) B = as.numeric(delta[Delta[i,2]]) C = as.numeric(delta[Delta[i,3]]) D = as.numeric(delta[Delta[i,4]]) data

I'm running a huge number of regressions in a loop, so I tried lm.fit for a speedup. However, I would like to be able to calculate the t-stats for the coefficients. Does anyone have some functions for calculating the regression summary stats of an lm.fit object? Thanks, Whit

Hi, pretty good job you are doing with Samba... I have just downloaded Samba 2.0.4 and I have a problem trying to compile it. I have configured the "configure" file and ran it (./configure). When I type make, I can see all the different modules compiling but I have an error with the /source/lib/system.c file. It is concerning the timeval struct (which I concluded must be a system

My question is about the "Signif. codes" , the output when I run matcoef =cbind(fit$par, se.coef,tval,2*(1-pnorm(abs(tval)))) dimnames(matcoef)=list(names(tval),c("Estimate","Std.Error","t value","pr(>|t|)")) cat("\nCoefficient(s):\n") printCoefmat(matcoef, digits=4, signif.stars = TRUE) Coefficient(s): Estimate

...tputs normalized coefficients ( coef(x)*sdv(x)/sdv(y) ). now, a formula is an object, and I cannot see how to extract the variables for obtaining sdv's. the intent is to write something like my.print.lm( formula ) { model <- lm(formula); coefs <- (t(summary.lm(model)))[1,]; tvals <- (t(summary.lm(model)))[3,]; for (i in 1:length( formula.contents.length ) ) { normcoefs[i] <- coefs[i]*sd( formula.coef[i] ) /sd( formula.yvar ); } # now I can do nice printing } my.print.lm ( y~x+z ); or something like it. If this is not easy, please just tell me. I j...

Hello, I am interested in using nlme to model repeated measurements, but I don't seem to get good CIs. With the code below I tried to generate data sets according to the model given by equations (1.4) and (1.5) on pages 7 and 8 of Pinheiro and Bates 2000 (having chosen values for beta, sigma.b and sigma similar to those estimated in the text). For each data set I used lme() to fit a model,

This patch introduces a handful of new options, I mentioned earlier in: http://www.mail-archive.com/nut-upsdev at lists.alioth.debian.org/msg02088.html See the large commit message in the follow-up for the details and rationale. I realize it's a bit larger diff - so if it's required I can split it into few smaller ones. Michal Soltys (1): APC smart driver update and new features.