similar to: predict nbinomial glm

I''ve setup two models, 1 and 2, that are associated by has_and_belongs_to_many. I''m trying to get an attribute from model_1 to use in a method in model_2. When I use the code below, I get an error saying ''undefined method model_1_id''. What am I missing? Thanks! Model_2.rb Class Model_2 < ActiveRecord::Base ... has_and_belongs_to_many :model_1 def

Dear R-helpers, I try to perform glm's with negative binomial distributed data. So I use the MASS library and the commands: model_1 = glm.nb(response ~ y1 + y2 + ...+ yi, data = data.frame) and predict(model_1, newdata = data.frame) So far, I think everything should be ok. But when I want to perform a glm with a subset of the data, I run into an error message as soon as I want to predict

Hi R users, The nlme library enabled several alternate error structures useful for longitudinal or repeated-measures data. For example, a continuous AR(1) process: model_2 = update(model_1, correlation = corCAR1(form = ~ time | subject)) Does anybody know if this is available in lme4? Thank you Ben -- View this message in context:

Hello, all, I have a dataframe of three rows and umpteen columns. I want to show the maximum, minimum, and median with a vertical line and a central dot (I'd use a boxplot, but with only three data points, that's overkill; I can't just use points, because of overlap and some of the other data plotted on the graph). This works: > boxplot(data_frame,

Ok, so basically I have a dataframe named data_frame data_frame contains: startdate startprice endpricethreshold1 endpricethreshold2 endpricethreshold3 all of these endpricethresholds are true/false binary vectors. They are true or false depending on whether the endprice was above or below whatever the endpricethreshold is. now I want to try to use lets say the general linear model to have

Hi I have a data.frame with the following numbers (first column are month numbers) 07,0,0,0,0.315444056314174,0,0,0,12.5827462764176,0.079194498691732, 0.0280828101707015,0,0.0695808222378877 08,0,0,105600,0.393061160316545,0,0,0,8.95551253153947,0.0880023174276553, 0.285714285714286,0,0.0669139911789158 09,0,0,0,0,12.5,0,0,13.5135887094281,0.0557531529154668,0,0, 0.0487526139182026

Dear all, I am trying to evaluate the optimisation behaviour of a function. Originally I have optimised a model with real data and got a set of parameters. Now I am creating simulated data sets based on these estimates. With these simulations I am estimating the parameters again to see how variable the estimation is. To this end I have written a loop which should generate a new simulated data

New years greetings. I have been setting up a function to generate multiple jpeg charts. When the calls are issued at the interactive console, the jpeg files are generated without an issue. When I try to issue the same calls from a function, some chart files are empty. It appears to only be related to trellis charts. Any help to troubleshoot this is appreciated. Regards, -mike R version

Hi, I am trying to get information about factors from a C-program. As I see, the factors are basically integers with attribute ,,levels''. But unfortunately I am not been able to read the levels information. I am using: SEXP variable, levels; ... variable = VECTOR_ELT( data_frame, j); switch( TYPEOF( variable)) { case INTSXP: if( isFactor( VECTOR_ELT( data_frame,

To whom it may concern: I have a question about how to appropriately conduct an lmer analysis for negative binomially distributed data. I am using R 2.2.1 on a windows machine. I am trying to conduct an analysis using lmer (for non-normally distributed data and both random and fixed effects) for negative binomially distributed data. To do this, I have been using maximum likelihood,

Hello, I've an error recently. ggplot(data = mtcars, aes(x= wt, y= mpg)) + geom_line() Error: Found object is not a stat. > sessionInfo() R version 3.4.2 (2017-09-28) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 16.04.3 LTS Matrix products: default BLAS: /usr/lib/openblas-base/libblas.so.3 LAPACK: /usr/lib/libopenblasp-r0.2.18.so locale: [1] LC_CTYPE=tr_TR.UTF-8

I was not able to reproduce this problem. I tried two environments 1. Ubuntu 14.04.5 LTS, R version 3.4.2 (same R version as yours) 2. Windows 10, same R version On Wed, Nov 8, 2017 at 9:50 AM, Zeki ?ATAV <zcatav at gmail.com> wrote: > Hello, > I've an error recently. > > ggplot(data = mtcars, aes(x= wt, y= mpg)) + geom_line() > Error: Found object is not a stat. >

As an R beginner, I feel brain dead today as I can not find the answer to a relatively simple question. Given a array of string values, for example lets say "mary", "bob", "danny", "sue", and "jane". I am trying to determine how to perform a logical test to determine if a variable is an exact match for one of the string values in the array

Hi, I became a little bit confused when working with the Wilcoxon test in R. As far as I understood, there are mainly two versions: 1) wilcox.test{stats}, which is the default and an approximation, especially, when ties are involved 2) wilcox_test{coin}, which does calculate the distribution _exactly_ even, with ties. I have the following scenario: #---BeginCode--- # big example size = 60

I get the same result as Eric? withR version 3.4.2 (2017-09-28) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 17.04 It looks like you have "tidyverse" loaded so I tried it with just ggplot2 loaded and with tidyverse loaded.? On Wednesday, November 8, 2017, 4:16:14 AM EST, Eric Berger <ericjberger at gmail.com> wrote: I was not able to reproduce this

Dear R helpers, I have the following model model_1<-glm(y~A+B+C+E+A:D,contrasts=list(D=contrasts_D),data=mydata,na.action=na.omit) with: options(contrasts=c("contr.sum", "contr.poly")) A,B and E are 2-levels factor, C is covariate, D is 20 levels factor with 10 in relation with the first levels of factor A, the other in relation with the second levels of factor A

Hi, I am trying to study R internal behaviour. So long, I have not succeeded to access the value of R strings from C. I use: void salvesta_tabel( SEXP data_frame, SEXP file ) { printf( "nimi %d\n", (R_CHAR)( file)); } and from the R side: salvesta.tabel <- function (x, file = "") { .Call( "salvesta_tabel", x, file) } When calling

Hi all, Assume I have a data frame with numerical and factor variables that I got through merging various other data frames and subsetting the resulting data frame afterwards. The number levels of the factors seem to be the same as in the original data frames, probably because subset() calls [.factor without drop = TRUE (that's what I gather from scanning the mailing lists). I wonder if

Question: How can I get access to the bias value of a boot statistic? Details: Boot function: boot(data, statistic, R, sim="ordinary", stype="i", strata=rep(1,n), L=NULL, m=0, weights=NULL, ran.gen=function(d, p) d, mle=NULL, ...) When I create an object, containing the bootstrap statistic (object <- boot (....))I can call it and will get an output

Hello Ulrik, Can you please explain this code means how and what this code is doing because I'm not able to understand it, if you can explain it i can use it in future by doing some Lil bit manipulation. Thanks data_help <- data_help %>% mutate(Purchase_ID = 1:n()) %>% group_by(Purchase_ID) %>% do(split_items(.)) cat_help %>% gather("Foo",