r

问题 I need to extract the posterior estimates and intervals for a random effect from my model. For illustrative purposes, a similar dataset to the one I am using would be the ChickWeight dataset in base R. The way I extract the posterior estimates and intervals for my fixed effects is like so: #load package library(lme4) #model m.surv<-lmer(weight ~ Time + Diet + (1|Chick), data=ChickWeight) #load packages library(MCMCglmm) library(arm) #set up for fixed effects sm.surv<-sim(m.surv) smfixef.surv

问题 I have a data frame with a variable containing elements to drop if they match to an element in another variable - see a small example below: df <- data.frame(pair = c(1, 1, 2, 2, 3, 3), animal = rep(c("dog", "cat"), 3), value = seq(1, 12, 2), drop = c("no", "no", "dog", "dog", "cat", "cat")) pair animal value drop 1 1 dog 1 no 2 1 cat 3 no 3 2 dog 5 dog 4 2 cat 7 dog 5 3 dog 9 cat 6 3 cat 11 cat I'm trying to want to filter the data frame according to whether the value of animal matches the

问题 I need to extract the posterior estimates and intervals for a random effect from my model. For illustrative purposes, a similar dataset to the one I am using would be the ChickWeight dataset in base R. The way I extract the posterior estimates and intervals for my fixed effects is like so: #load package library(lme4) #model m.surv<-lmer(weight ~ Time + Diet + (1|Chick), data=ChickWeight) #load packages library(MCMCglmm) library(arm) #set up for fixed effects sm.surv<-sim(m.surv) smfixef.surv

问题 I can't figure out how to make a table subplot work properly using R and Plotly. The following demonstrates what I mean. I have two plots, one scatter and one table. Using the subplot function, the table plot does not behave as expected. I either lose interactivity on the scatter plot, or have overlapping scatter/table plots. Please let me know if I'm missing something or if this is a bug. I'm using plotly version 4.9.0 Thanks in advance! library(plotly) df <- data.frame(x = 1:10, y = 1:10)

问题 I'm currently trying to get my head around the differences between stat_* and geom_* in ggplot2 . (Please note this is more of an interest/understanding based question than a specific problem I am trying solve). Introduction My current understanding is that is that the stat_* functions apply a transformation to your data and that the result is then passed onto the geom_* to be displayed. Most simple example being the identity transformation which simply passes your data untransformed onto the

问题 I've got a plot with a fairly wide y-axis label, so I want to adjust the title to the left so that it's flush with the label rather than the axis (like this question) but the twist is that I have a multiline title. I've been using hjust, but it adjusts the two lines differently. For example ggplot(mtcars,aes(x=wt,y=mpg))+ geom_point()+ ggtitle("Figure: My long and winding title\nthat goes on and on and on") + ylab("My long label") + theme_bw() + theme(plot.title = element_text(size=16, hjust=

问题 I've got a plot with a fairly wide y-axis label, so I want to adjust the title to the left so that it's flush with the label rather than the axis (like this question) but the twist is that I have a multiline title. I've been using hjust, but it adjusts the two lines differently. For example ggplot(mtcars,aes(x=wt,y=mpg))+ geom_point()+ ggtitle("Figure: My long and winding title\nthat goes on and on and on") + ylab("My long label") + theme_bw() + theme(plot.title = element_text(size=16, hjust=

问题 In R often the NULL value is used as default. Using Python and RPy2, how can one explicitly provide a NULL argument? None is not convertible ( NotImplementedError ), a string 'NULL' will just be converted to a string and result in an error during execution. Take the following example using the tsintermittent package: import numpy as np from rpy2.robjects.packages import importr from rpy2.robjects import numpy2ri numpy2ri.activate() tsintermittent = importr('tsintermittent') crost =

问题 I am trying to run the osmar package on my windows 10, R 3.4.2, and have correctly installed osmosis. However when I try to run the code: >library("osmar") > >src <- osmsource_osmosis(file = "c:/users/ben_c/Documents/FYP/FYP_NL_Map/muenchen.osm", osmosis = "osmosis") > > >nl_bbox <- center_bbox(11.575278, 48.137222, 3000, 3000) > >nl <- get_osm(nl_bbox, src) > >plot(nl) I get the warning, after osmosis has run: >Error in file(con, "r") : cannot open the connection >In addition: Warning

问题 In R, what would be the best way to separate the following data into a table with 2 columns? March 09, 2018 0.084752 March 10, 2018 0.084622 March 11, 2018 0.084622 March 12, 2018 0.084437 March 13, 2018 0.084785 March 14, 2018 0.084901 I considered using a for loop but was advised against it. I do not know how to parse things very well, so if the best method involves this process please be as clear as possible. The final table should look something like this: https://i.stack.imgur.com/u5hII