similar to: Extract information from the summary of 'lm'

Colleagues, Here is my reproducible code for a graph using geom_smooth set.seed(55) scatter_data <- tibble(x_var = runif(100, min = 0, max = 25) ?????????????????????? ,y_var = log2(x_var) + rnorm(100)) library(ggplot2) library(cowplot) ggplot(scatter_data,aes(x=x_var,y=y_var))+ ? geom_point()+ ? geom_smooth(se=TRUE,fill="blue",color="black",linetype="dashed")+

?s 05:17 de 12/08/2023, Thomas Subia via R-help escreveu: > Colleagues, > > Here is my reproducible code for a graph using geom_smooth > set.seed(55) > scatter_data <- tibble(x_var = runif(100, min = 0, max = 25) > ?????????????????????? ,y_var = log2(x_var) + rnorm(100)) > > library(ggplot2) > library(cowplot) > > ggplot(scatter_data,aes(x=x_var,y=y_var))+

Dear R-users Please excuse me if this topic has been covered before, but I was unable to find anything relevant by searching I am currently doing a comparison of two biological variables that have a highly significant linear relationship. I know that the p-value of linear regression is not so interesting in itself, but this particular value does raise a question. How does R calculate

G'day Thomas, On Sat, 12 Aug 2023 04:17:42 +0000 (UTC) Thomas Subia via R-help <r-help at r-project.org> wrote: > Here is my reproducible code for a graph using geom_smooth The call "library(tidyverse)" was missing. :) > I'd like to add a black boundary around the shaded area. I suspect > this can be done with geom_ribbon but I cannot figure this out. Some >

Rhelpers: Having a problem solving this. I have an xyplot call that looks like this: print(xyplot(temp_species_EAM_Pred_Pop$x+temp_species_NULL_Pred_Pop$x~temp_species_EAM_Pred_Pop$Action,main=current_species, xlab="Action",ylab="Predicted Pop", xlim=c(xmin,xmax),ylim=c(ymin,ymax),

Apologies if this has been gone over, but I believe I have checked the intertubes more than a bit..... I am using libvirt and have vms booting under an OVMF.fd to use an efi firmware. I can create vms, linux ubuntu, and they will boot up. However, everytime I reboot am I dropped into the default efi shell provide by the tianocore build. Then I must walk the FS to the booting efi app and run, in

Thanks VERY MUCH for all the info and help! Apologies for the extreme delay. I got distracted by other threads that forced out this work to later date. Also some frustration as well. ;) I completely missed this update. Apologies and thanks Will be diving back into this shortly! On Thu, Mar 24, 2016 at 3:57 PM, Laszlo Ersek <lersek@redhat.com> wrote: > On 03/21/16 19:53, jsl6uy js16uy

On Mon, 2016-03-21 at 13:53 -0500, jsl6uy js16uy wrote: > for this host....my nvram setting look like >   <os> >     <type arch='x86_64' machine='pc-i440fx-2.5'>hvm</type> >     <loader readonly='yes' type='pflash'>/home/xyz/OVMF.fd</loader> >     <nvram

On 03/21/16 19:53, jsl6uy js16uy wrote: > Apologies if this has been gone over, but I believe I have checked the > intertubes more than a bit..... > > I am using libvirt and have vms booting under an OVMF.fd to use an efi > firmware. I can create vms, linux ubuntu, and they will boot up. > However, everytime I reboot am I dropped into the default efi shell > provide by the

Hi, I'm very new to working with sparse matrices and would like to know how I can column permute a sparse matrix. Here is a small example: > M1 <- > spMatrix(nrow=5,ncol=6,i=sample(5,15,replace=TRUE),j=sample(6,15,replace=TRUE),x=round_any(rnorm(15,2),0.001)) > M1 5 x 6 sparse Matrix of class "dgTMatrix" [1,] 2.983 . 1.656 5.003 . . [2,] .

> tmp <- data.frame(y=rnorm(12), a=factor(rep(letters[1:4],3))) > tmp y a 1 -0.60866099 a 2 0.55500538 b 3 0.12231693 c 4 -0.24613790 d 5 -0.09253593 a 6 -1.54652581 b 7 0.17204210 c 8 -1.22778942 d 9 1.22151194 a 10 -0.43982577 b 11 -1.25444287 c 12 -0.97251060 d > tmp.aov <- aov(y ~ a, data=tmp) > summary(tmp.aov) Df Sum Sq Mean Sq F value

I need to extract t-test statistics from glm(). For example, Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 46.2199 11.6310 3.974 0.000106 *** Var1 1.0440 0.5948 1.755 0.081088 . Var2 -0.4717 2.0257 -0.233 0.816178 Var3 0.2376 0.1454 1.635 0.104024 And I want to put all the t-values (and if

Dear forum members, How can I force a negative slope in a linear regression even though the slope might be positive? I will need it for the purpose of determining the trend due reasons other than biological because the biological (genetic) trend is not positive for these data. Thanks. Julia Example of the data: [1] 1.254 1.235 1.261 0.952 1.202 1.152 0.801 0.424 0.330 0.251 0.229

How might one calculate standard deviation, row-wise, for the numeric values in a data frame such as this one V1 V2 V3 V4 V5 1 rs11089130 0.4565 0.4574 0.4569 0.4572 2 rs738829 0.6548 0.6519 0.6448 0.6549 3 rs915674 0.7503 0.7500 0.7517 0.7502 and place the standard deviation in a 6th column called “std_dev”? Regards, Jim [[alternative HTML version deleted]]

Hi, I am about to write functions for multivariate kernel densitiy estimation with mixed categorical and continuous date (accoring to Jeff Racine and Qi Li), and the leave-one-out window esitmation needs a lot of computation. I am now optimizing the code performance and therefore fhe following questions: As R uses call-by-value for functions, is it computational expensive to pass large matrices

I have a data set for different time intervals. The data has three comment lines before data for each time interval. For each time interval there are 500 data points. I want to change the dataset such that I have the following format: t1 t2 t3 ................ 0.00208 0.00417 0.00625 ................. a1 a2 a3 ...................

Dear R-users, I'm studing a DB, structured like this (just a little part of my dataset): _____________________________________________________________________________________________________________ Site Latitude Longitude Year Tot-Prod Total_Density dmp Dendoudi-1 15.441964 -13.540179 2005 3271.16 1007 16993.25 Dendoudi-2 15.397321 -13.611607

hello for exampl, i have this programme # Generating data which are right truncated library(DTDA) library(splines) library(survival) n<-25 X<-runif(n,0,1) V<-runif(n,0.75,1) for (i in 1:n){ while (X[i]>V[i]){ X[i]<-runif(1,0,1) V[i]<-runif(1,0.75,1) }} res<-lynden(X=X,U=NA, V=V, boot=TRUE) attach(res) temps = time M_i = n.event L_t = res

Dear R users, I have panel data on the amount of money spent by travellers from 8 origin countries in 4 destinations. I would like to carry out analysis for destinations, origins and time. However, it seems to me that the package "plm" can only esitmate two-way panel data (indexed by a two-dimensional array). Any suggestions would be greatly appreciated. Thank you. Best regards,

Hi list, I have a problem which I was stuck on for a while, and after many days still cannot find a solution to. I have a matrix, measuring m X n. An example matrix will be this: >dput(sample) structure(c(2315101, 2315102, 2315103, 2315104, 2315105, 2315107, 2315108, 2315110, 2315112, 2315114, 2315116, 2315118, 2315120, 2315122, 2315124, 2315126, 2315127, 2315128, 2315130, 2315131, 2315132,