From: Douglas Bates <bates_at_stat.wisc.edu>

Date: Thu, 15 May 2008 08:39:56 -0500

R-help_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 15 May 2008 - 18:31:58 GMT

Date: Thu, 15 May 2008 08:39:56 -0500

Did you happen to notice the part at the bottom of every message about "provide commented, minimal, self-contained, reproducible code"?

Considering that the result you quote from "251" has 2 coefficients and the result from "171" has 3 coefficients one might contemplate the possibility that you are fitting different models or perhaps using different data. However we can't verify anything about the causes because we have no data regarding the problem.

Perhaps you are Brian Ripley's evil twin trying to provoke him. I would say that references to a nonexistent version "171" are deliberately provocative. ("251" could be considered a lazy person's attempt at 2.5.1 but "171" which presumably came after "251" doesn't make any sense to me.)

On Thu, May 15, 2008 at 7:05 AM, e-letter <inpost_at_gmail.com> wrote:

> Readers,

*>
**> Using version 251 I tried the following command:
**>
**> lm(y~a+b,data=datafile)
**>
**> Resulting in, inter alia:
**> ...
**> coefficients
**> (intercept) a
**> 1.2 3.4
**>
**> Packages installed:
**> acepack ace() and avas() for selecting regression
**> transformations
**> adlift An adaptive lifting scheme algorithm
**> akima Interpolation of irregularly spaced data
**> alr3 Methods and data to accompany Applied Linear
**> Regression 3rd edition
**> car Companion to Applied Regression
**> coda Output analysis and diagnostics for MCMC
**> drc Analysis of dose-response curves
**> EbayesThresh Empirical Bayes thresholding and related
**> methods
**> emplik Empirical likelihood ratio for
**> censored/truncated data
**> gllm Generalised log-linear model
**> glmc Fitting Generalized Linear Models Subject to
**> Constraints
**> glmmML Generalized linear models with clustering
**> glmpath L1 Regularization Path for Generalized Linear
**> Models and Cox Proportional Hazards Model
**> HydroMe Estimation of Soil Hydraulic Parameters from
**> Experimental Data
**> JGR JGR - Java Gui for R
**> lmtest Testing Linear Regression Models
**> locfit Local Regression, Likelihood and Density
**> Estimation.
**> mvtnorm Multivariate Normal and t Distributions
**> NISTnls Nonlinear least squares examples from NIST
**> nlme Linear and Nonlinear Mixed Effects Models
**> nlstools Tools for nonlinear regression diagnostics
**> nlt A nondecimated lifting transform for signal
**> denoising
**> nlts (non)linear time series analysis
**> nnls The Lawson-Hanson algorithm for non-negative
**> least squares (NNLS)
**> plotrix Various plotting functions
**> quantreg Quantile Regression
**> Rcmdr ** No title available (pre-2.0.0 install?) **
**> sandwich Robust Covariance Matrix Estimators
**> SparseM Sparse Linear Algebra
**> sspline Smoothing Splines on the Sphere
**> zoo Z's ordered observations
**>
**> Packages in library '/usr/lib/R/library':
**> base The R Base Package
**> boot Bootstrap R (S-Plus) Functions (Canty)
**> class Functions for Classification
**> cluster Cluster Analysis Extended Rousseeuw et al.
**> codetools Code Analysis Tools for R
**> datasets The R Datasets Package
**> foreign Read Data Stored by Minitab, S, SAS, SPSS,
**> Stata, Systat, dBase, ...
**> graphics The R Graphics Package
**> grDevices The R Graphics Devices and Support for Colours
**> and Fonts
**> grid The Grid Graphics Package
**> KernSmooth Functions for kernel smoothing for Wand & Jones
**> (1995)
**> lattice Lattice Graphics
**> MASS Main Package of Venables and Ripley's MASS
**> methods Formal Methods and Classes
**> mgcv GAMs with GCV smoothness estimation and GAMMs
**> by REML/PQL
**> nlme Linear and Nonlinear Mixed Effects Models
**> nnet Feed-forward Neural Networks and Multinomial
**> Log-Linear Models
**> quadprog Functions to solve Quadratic Programming
**> lattice Lattice Graphics
**> MASS Main Package of Venables and Ripley's MASS
**> methods Formal Methods and Classes
**> mgcv GAMs with GCV smoothness estimation and GAMMs
**> by REML/PQL
**> nlme Linear and Nonlinear Mixed Effects Models
**> nnet Feed-forward Neural Networks and Multinomial
**> Log-Linear Models
**> quadprog Functions to solve Quadratic Programming
**> Problems.
**> rcompgen Completion generator for R
**> rpart Recursive Partitioning
**> spatial Functions for Kriging and Point Pattern
**> Analysis
**> splines Regression Spline Functions and Classes
**> stats The R Stats Package
**> stats4 Statistical Functions using S4 Classes
**> survival Survival analysis, including penalised
**> likelihood.
**> tcltk Tcl/Tk Interface
**> tools Tools for Package Development
**> utils The R Utils Package
**>
**> When using version 171 I entered the same command:
**>
**> lm(y~a+b,data=datafile)
**>
**> Resulting in, inter alia:
**> ...
**> coefficients
**> (intercept) a b
**> 5.6 7.8 9.01
**>
**> Packages installed:
**> base The R base package
**> boot Bootstrap R (S-Plus) Functions (Canty)
**> class Functions for classification
**> cluster Functions for clustering (by Rousseeuw et al.)
**> ctest Classical Tests
**> eda Exploratory Data Analysis
**> foreign Read data stored by Minitab, S, SAS, SPSS,
**> Stata, ...
**> grid The Grid Graphics Package
**> KernSmooth Functions for kernel smoothing for Wand &
**> Jones (1995)
**> lattice Lattice Graphics
**> lqs Resistant Regression and Covariance Estimation
**> MASS Main Library of Venables and Ripley's MASS
**> methods Formal Methods and Classes
**> mgcv Multiple smoothing parameter estimation and
**> GAMs by GCV
**> modreg Modern Regression: Smoothing and Local Methods
**> mva Classical Multivariate Analysis
**> nlme Linear and nonlinear mixed effects models
**> nls Nonlinear regression
**>
**> lqs Resistant Regression and Covariance Estimation
**> MASS Main Library of Venables and Ripley's MASS
**> methods Formal Methods and Classes
**> mgcv Multiple smoothing parameter estimation and
**> GAMs by GCV
**> modreg Modern Regression: Smoothing and Local Methods
**> mva Classical Multivariate Analysis
**> nlme Linear and nonlinear mixed effects models
**> nls Nonlinear regression
**> nnet Feed-forward neural networks and multinomial
**> log-linear models
**> rpart Recursive partitioning
**> spatial functions for kriging and point pattern
**> analysis
**> splines Regression Spline Functions and Classes
**> stepfun Step Functions, including Empirical
**> Distributions
**> survival Survival analysis, including penalised
**> likelihood.
**> tcltk Tcl/Tk Interface
**> tools Tools for package development
**> ts Time series functions
**>
**> Why do I get different results when entering the same equation
**> command? The correct answer was obtained using the older version of
**> the software, so I want to replicate using the new version, which is
**> installed onto a new pc that I am using. Any advice.
**>
**> Yours,
**>
**> rhelp_at_conference.jabber.org
**>
**> ______________________________________________
**> R-help_at_r-project.org mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
**> and provide commented, minimal, self-contained, reproducible code.
**>
*

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 15 May 2008 - 18:31:58 GMT

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