similar to: Adding predicted values as a new variable in a data frame

R-experts, I have fitted many different lines. The fast-tau estimator (yellow line) seems strange to me?because this yellow line is not at all in agreement with the other lines (reverse slope, I mean the yellow line has a positive slope and the other ones have negative slope). Is there something wrong in my R code ? Is it because the Y variable is 1 vector and should be a matrix ? Here is the

Hi there, I am really new to statistics in R and statistics itself as well. My situation: I ran a lot of OLS regressions with different independent variables. (using the lm() function). After having done that, I know there is endogeneity due to omitted variables. (or perhaps due to any other reasons). And here comes the Hausman test. I know this test is used to identify endogeneity. But what I

You need to pay attention to the documentation more closely. If you don't know what something means, that is usually a signal that you need to study more... in this case about the difference between an input variable and a design (model) matrix. This is a concept from the standard linear algebra formulation for regression equations. (Note that I have never used RobPer, nor do I regularly

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,

Dear R-helpers, let us assume, that I have the following dataset: a <- rnbinom(200, 1, 0.5) b <- (1:200) c <- (30:229) d <- rep(c("q", "r", "s", "t"), rep(50,4)) data_frame <- data.frame(a,b,c,d) In a first step I run a glm.nb (full code is given at the end of this mail) and want to predict my response variable a. In a second step, I would

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

I have a puzzle.... When I include an interaction in the model, many predicted probabilities are above 1. Is that a problem with my model? I thought the predicted prob can't be bigger than 1... Any help would be really appreciated! Thanks! K. reg1<-glm(pyea~male+edu+married+inc+relig+factor(time)+ factor(time)*male, data=mydata, family=binomial(link="logit"))

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

On 31/03/2018 11:57 AM, varin sacha via R-help wrote: > Dear R-experts, > > Here below my reproducible R code. I want to add many straight lines to a plot using "abline" > The last fit (fast Tau-estimator, color yellow) will not appear on the plot. What is going wrong ? > Many thanks for your reply. > It's not quite reproducible: you forgot the line to create

Hello. I'm trying to set up a vacation autoresponder but up to now, no success. I'm using dovecot managedsieve to set up the new filter and to my understanding it works correctly and it creates in the user's home the link .dovecot.sieve that points to sieve/managesieve.sieve ~$ cat .dovecot.sieve require ["date","relational","vacation"]; #

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

Forgive me if I'm missing something obvious, but it seems that a number of core instructions—I'm specifically running in to `atomicrmw`, `fence`, and `cmpxchg` at the moment—cannot be constructed from the C bindings, and are therefore also inaccessible to the OCaml bindings. There are opcodes for each of these in the llvm-c/Core.h, but there seems to be no way to construct them. Is there

Hi R people, I have a very basic question to ask - I'm sorry if it's been asked before, but I searched the archives and could not find an answer. All the examples I found were much more complicated/nuanced versions of the problem - my question is much more simple. I have data with multiple, nested fixed effects (as I understand it, fixed effects are specified by the experimental design

Dear colleagues, I have a question regarding controlling the jitter when plotting predictions in the rms package. Below I've simulated some data that reflect what I'm working with. The model predicts a continuous variable with an ordinal score, a two-level group, and a continuous covariate. Of primary interest is a plot of the group by score interaction, where the score is the ordinal

Here is my model with interaction terms and control variables (I changed variables names for easy read): reg1 <- lm(y ~ x1*x2*x3 +control1 + control2 + control3) x1 ranges from 0 to 6; x2 from 0 to 5; and x3 from 0 to 4. All three are discrete ordinal variables; but I will treat them as continuous variables. (a) How can I see the predicted values of y for each of these scenarios (210

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

How soon would I need to submit a patch for this for it to have a comfortable shot at making it into the 3.2 release? On Sep 14, 2012, at 8:05 PM, Eric Christopher <echristo at apple.com> wrote: > > On Sep 14, 2012, at 4:53 PM, Jonathan Ragan-Kelley <jrk at csail.mit.edu> wrote: > >> Is there a reason these should be omitted? > > Not in particular. Things are

Hi, See below I reply your message for <https://stat.ethz.ch/pipermail/r-help/2008-April/160966.html>[R] predict.glm & newdata posted on Fri Apr 4 21:02:24 CEST 2008 You say it ##works fine but it does not: if you look at the length of yhat2, you will find 100 and not 200 as expected. In fact predict(reg1, data=x2) gives the same results as predict(reg1). So I am still looking for

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

Hi all, In several of our tests, I have noticed that the register allocator allocates to virtual registers in a different order when compiling with the clang option -g. Before entering the register allocator, the code is identical when compiling with and without -g (with the exception of " DBG_VALUE" instructions). The only difference I can see is the value assigned to the slot index