similar to: Follow Up To: Splitting the left and right hand terms of a formula

Let's say I have the following formula: a.formula <- x ~ y + z I want to extract the left and right-hand sides of the function so that I have two character vectors like the ones you would create using the following assignments: left.hand.side <- "x" right.hand.side <- c("y", "z") One way to do this follows: left.hand.side <-

hello all, I am trying to use the function getCovariateFormula(nlme) in conjunction with the library lme4. When I load both packages I get the following message and the getCovariateFormula function no longer works: library(nlme) library(lme4) Attaching package 'lme4': The following object(s) are masked from package:nlme : contr.SAS getCovariateFormula

I found that predict.gnls failed with a wierd error message about a non-numeric argument to a binary vector in one of three nearly identical uses. Error in Inh/Ki : non-numeric argument to binary operator (Inh and Ki are arguments to the function used in the formula for the object whose predictions were requested). It turns out that the problem is in getCovariateFormula(). The final line in

Hello all, Consider the following problem: There is a matrix of probabilities: > set.seed(1) > probs <- array(abs(rnorm(25, sd = 0.33)), dim = c(5,5), dimnames = list(1:5, letters[1:5])) > probs a b c d e 1 0.21 0.27 0.50 0.0148 0.303 2 0.06 0.16 0.13 0.0053 0.258 3 0.28 0.24 0.21 0.3115 0.025 4 0.53 0.19 0.73 0.2710 0.656 5 0.11 0.10 0.37 0.1960

Hi everybody, as you may be aware the function augPred.lme does not work as soon as the covariate is a factor. The problem lies in the line newprimary <- seq(from = minimum, to = maximum, length.out = length.out) which does not make sense for factors. I think augPred.lme can be useful for models with a factor covariate as well. Thus, I propose to change the code to: augPred.lme <-

Hi, I guess this is a final plea, and maybe this should go to R-help but here goes. I am writing a set of functions for calibration and prediction, and to calculate standard errors and intervals I need the variance function to be evaluated at new prediction points. So for instance fit<-gnls(Y~SSlogis(foo,Asym,xmid,scal),weights=varPower())

Hello, I'm developing a GUI in R that will be used to monitor financial portfolio performance. The GUI will be distributed as an R package. So far, I've decided to use the "cairoDevice", "RGtk2", "gWidgets", and "gWidgetsRGtk2" packages to develop the GUI. I am trying to decide what would be the best way to structure the GUI would be. I've

Hello, I am having a problem specifying the correlation structure in lme which leads to the error: Error in getCovariate.corSpatial(object, data = data) : Cannot have zero distances in "corSpatial". I have specified a grouping variable which is the only fix I could find by searching this error on R-help. ISee the below example. When my samples (tran) - which are transects

Hi, I cannot seem to get lme4 to work. I have installed the lme4 and Matrix package with apt-get. and both can be found in /usr/lib/R/site-library. When I tried an example for lmer, R could not find the function lmer(), > library(lme4) Attaching package: 'lme4' The following object(s) are masked from package:nlme : getCovariateFormula getResponseFormula

Dear listers, I am trying to model the distribution of fox density over years in the Doubs department. Measurements have been taken on 470 plots in March each year and georeferenced. Average density is supposed to be different each year. In a first approach, I would like to use a general model of this type, taking spatial correlation into account:

Hi, I have been using the function lme() of the package nlme to model grouped data that is auto-correlated in time and in space (the data was collected on different days via a moving monitor). I am aware that I can use the correlation classes corCAR1 and corExp (among other options) to model the temporal and spatial components of the auto-correlation. However, as far as I can tell, I can only

Hello, Does anyone know of a function that will determine whether or not a formula object has a left hand side? I.e., can differentiate between y ~ x + z and ~ x + z Perhaps I'm overlooking the obvious... Thanks!

The lattice package uses special logic to allow for multiple left-hand-side variables in a formula, e.g. y1 + y2 ~ x. Is there an elegant way to do this outside of lattice? I'm trying to implement a data summarization function that logically takes multiple dependent variables. The usual invocation of model.frame( ) causes R to try to do arithmetic addition to create a single dependent

Dear all, I am trying to define my own corStruct which is different from the classical one available in nlme. The structure of this correlation is given below. I am wondering to know how to continue with this structure by using specific functions (corMatrix, getCovariate, Initialize,...) in order to get a structure like corAR1, corSymm which will be working for my data. Thanks in advance.

Dea-R community. I'd like to draw your attention to an issue I have recently encountered while doing my current data analysis. I've got an unexpected (to me) result from the command: > augPred(lmList(my.object)), 'my.object' being a grouped data frame of class: > class(my.object) [1] "nfnGroupedData" "nfGroupedData" "groupedData"

Why when I assign 0 to an element of an integer vector does the type change to numeric? Here is a particularly perplexing example: > v <- 0:10 > v [1] 0 1 2 3 4 5 6 7 8 9 10 > class(v) [1] "integer" > v[1] <- 0 > class(v) [1] "numeric" #!! > -- View this message in context:

Why when I assign 0 to an element of an integer vector does the type change to numeric? Here is a particularly perplexing example: > v <- 0:10 > v [1] 0 1 2 3 4 5 6 7 8 9 10 > class(v) [1] "integer" > v[1] <- 0 > class(v) [1] "numeric" #!! > -- View this message in context:

I have two tables: table_1: tab1_id, other_id table_2: id, tab2_id, something_else I would like to specify a has_one mapping from table_1 to table_2 but specifying that the join is based on (table_2.tab2_id = table_1.other_id). I am half way there with: class Table1 < ActiveRecord::Base set_table_name "table_1" set_primary_key "tab1_id" has_one :Table2, :class_name

Hello, I am using the package arules to generate association rules. I would like to restrict the rules so that in the left-hand side there's only one particular element, let's call it "potatoe". If I do this: rules <- apriori(dtm.mat, parameter = list(sup = 0.4, conf = 0.9,target="rules"), appearance = list(lhs = c("potatoe"))) I get "potatoe"

Is there a way to get subscripts and superscripts on the left hand side of a symbol? For example, oC or oF (degree Celsius or Fahrenheit) TIA Partha -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the