similar to: Efficient matrix computations

Hi, I have a dataframe containing a date object in the first column and numeric data in two other columns, for a total of three columns. I would like to plot the 2 numeric data columns against the dates in one window. How do I do this? It is easy to do if only one data series is to be plotted against a set of dates, but two or more datasets seems to be harder. Note: I have daily data where

Hi everyone, I am currently using the function optim() to maximize/minimize functions and I would like to see more output of the optimization procedure, in particular the numerical gradient of the parameter vector during each iteration. The documentation of optim() describes that the trace parameter should allow one to trace the progress of the optimization. I use the following command:

Dear list members; The code given below corresponds to the PCA-NIPALS (principal component analysis) algorithm adapted from the nipals function in the package chemometrics. The reason for using NIPALS instead of SVD is the ability of this algorithm to handle missing values, but that's a different story. I've been trying to find a way to improve (if possible) the efficiency of the code,

The function of crossprod in R puzzled me. I would like to calculate the cross product of two vectors. According to my text book, it defines like this: a = (ax, ay, az) b = (bx, by, bz) then, the cross product of a and b is: a X b = (ay*bz-az*by, az*bx-ax*bz, ax*by-ay*bz) It can also write in a determinant format. But the crossprod or tcrossprod function in R appeared not calculate the cross

In a newly downloaded version (today) of R-2-4-0alpha, with all packages from CRAN also installed today, I get: > library(Matrix) Erro en loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'Matrix' methods specified for export, but none defined: BIC, anova, coef, confint, deviance, fitted, fixef, formula, head, lmer, logLik, mcmcsamp, plot,

I am trying to build a package (GWASTools, submitted to Bioconductor) that uses the "sandwich" package. I have references to "sandwich" in DESCRIPTION: Imports: methods, DBI, RSQLite, sandwich, survival, DNAcopy and NAMESPACE: import(sandwich) In the code itself is a call to vcovHC: Vhat <- vcovHC(mod, type="HC0") I have sandwich version 2.2-7 installed.

Hello Is there any function to calculate White's standard errors in R in an NLS regression. The sandwich and car package do it but they need an lm object to calculate the error's. Does anyone have idea how to do it for an NLS object ? Regards The woods are lovely, dark and deep But I have promises to keep And miles before I go to sleep And miles before I go to sleep ----- [[alternative

Hi, I'm using maxlik with functions specified (L, his gradient & hessian). Now I would like determine some robust standard errors of my estimators. So I 'm try to use vcovHC, or hccm or robcov for example but in use one of them with my result of maxlik, I've a the following error message : Erreur dans terms.default(object) : no terms component Is there some attributes

Is there a way of reading in a file in a way that each line becomes a vector: for example: meals.txt breakfast bacon eggs sausage lunch sandwich apple marsbar crisps dinner chicken rice custard pie I want to read in this file and end up with 3 different vectors, one called breakfast which contains "bacon", "eggs", sausage" One called

Hi, I would like to estimate a panel model (small N large T, fixed effects), but would need "robust" standard errors for that. In particular, I am worried about potential serial correlation for a given individual (not so much about correlation in the cross section). >From the documentation, it looks as if the vcovHC that comes with plm does not seem to do autocorrelation, and the

Ted Harding said: > I can get the estimated RRs from > RRs <- exp(summary(GLM)$coef[,1]) > but do not see how to implement confidence intervals based > on "robust error variances" using the output in GLM. Thanks for the link to the data. Here's my best guess. If you use the following approach, with the HC0 type of robust standard errors in the

Hello, I am trying to extract an estimator for the bread of the sandwich function. I used bread(fitted model) however it seems that I have missed something as an error message "no applicable method for "bread" appears. My fitted model is a Spatial simultaneous autoregressive error model.(errorsarlm in spdep package) Can anyone please tell me what I might be doing wrong? Your

Dear All, After upgrading to R-2.4.0-dapper2 (my system is ubuntu 6.06 LTS), I often met problems when loading some packages like Matrix. Here is the details: > library(Matrix) Error in loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'Matrix' methods specified for export, but none defined: Arith, Math, Math2, +, %*%, Schur, as.matrix, chol,

Hi, I am relatively new to R; when creating functions, I run into problems with missing values. I would like my functions to ignore rows with missing values for arguments of my function) in the analysis (as for example is the case in STATA). Note that I don't want my function to drop rows if there are missing arguments elsewhere in a row, ie for variables that are not arguments of my

Hi, In one of my packages (maxLik), I would like to add an S3 method, where the generic function (estfun) is defined in another package (sandwich). Everything works fine if my package "Depends" on the other package and I import the generic function "estfun" from the "sandwich" package and define the new method in the NAMESPACE file. However, I prefer not to load the

Dear R-users, Is there a preferred method for testing whether a real symmetric matrix is positive definite? [modulo machine rounding errors.] The obvious way of computing eigenvalues via "E <- eigen(A, symmetric=T, only.values=T)$values" and returning the result of "!any(E <= 0)" seems less efficient than going through the LU decomposition invoked in

Hello, first of all: I'm new to R and have only used SPSS befor this (which can't do this at all...). I'm trying to output some regression results to latex. The regressions are normal OLS and I'm trying to output the results with standardized regression coefficients and t-statistics based on "Huber-White sandwich estimator for variance". The final result should be

Is anyone aware of a procedure to apply Newey-West corrections for autocorrelation to a SUR regression model? The SANDWICH package seems to be applicable only to LM or GLM models. Thanks, Richard Saba Department of Economics Auburn University Email: sabaric at auburn.edu

Dear R-Users: I am trying to find the robust (or sandwich) estimates of the standard error of fixed effects parameter estimates using the package "lmer2". In model-1, I used "robust=TRUE" on the other, in model-2, I used "robust=FALSE". Both models giving me the same estimates. So my question is, does the robust option works in lmer2 to get the robust estimates of

Dear All We've noticed that old (1.9.18x) versions of samba do not like very long ( over 1020 ish bytes ) valid user= lines. I assume that a 1k buffer is overrun. Yes, we have that many users for some shares. What is the limit in more recent samba's (2.2.x) - I know this is in the source - so if someone could point me in the right direction I'll go look (I am not a great C