similar to: Confused about a warning message

Hi there, Could someone help me with the following programming problem..? I have written a function that works for my intended purpose, but it is quite closely tied to a particular dataframe and the names of the variables in this dataframe. However, I'd like to use the same function for different dataframes and variables. My problem is that I'm not quite sure how to tell my function in

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

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 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

--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.

When I do t.test on two distributions (see example below), it outputs numerous data about the t.test. What I'd like to do is individually capture some of this data and assign it to other variables. However, I am unable to find anything in the help section. In the example below, the t value is -4.0441 and the p-value is 0.006771 How can I assign these values to two variables, let's

Dear R forum I have data.frame as df = data.frame(rate_name = c("USD_1w", "USD_1w", "USD_1w", "USD_1w", "USD_1m", "USD_1m", "USD_1m", "USD_1m", "USD_2m", "USD_2m", "USD_2m", "USD_2m",  "GBP_1w", "GBP_1w", "GBP_1w", "GBP_1w",

Hi there, I am not getting anywhere near a solution, so here is my question. I have searched the archives and didn't find a solution, but maybe my search didn't use the right words. So here it is: I have a dataframe with the following structure factor1 factor2 value In the (rather large) dataset I have to work on, there are some factor combinations missing, e.g. factor1 <-

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

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",

On Thu, Sep 11, 2008 at 6:14 PM, Villmow, Micah <Micah.Villmow at amd.com> wrote: > 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

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'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

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