Dear Sacha,
use glm() in this case. I'd rather code the covariable as TRUE / FALSE or
as a factor.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team
Dear Kelly,
Have a look at the renv package (https://CRAN.R-project.org/package=renv).
Once setup, your code reduces to renv::restore()
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH
Dear Debbie,
Have a look at the vignette of the ordinal package. Look for the equation
that defines \eta. And note the minus sign associated with \beta. You'll
need to find the equation used in HLM and compare it with the equation from
ordinal.
Best regards,
ir. Thierry Onkelinx
Statisticus
Dear Tracy,
Maybe a workshop of Data Carpentry (https://datacarpentry.org/) might be
relevant.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team
eth is not a dataframe but of the class rxlsx. You'll need to convert eth
into a dataframe.
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteits
. That is not a good idea. https://blog.datawrapper.de/dualaxis/
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality A
Dear Bruce,
I think this should be straightforward with tidyverse. If not please
provide a small reproducible data set with dput().
library(tidyverse)
count(Active, Time)
count(Active, Date, Time)
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government
You could use kable() from the knitr package.
kable(mytable, format = "latex", escape = FALSE)
\begin{tabular}{l}
\hline
$\beta_0$\\
\hline
aa\\
\hline
bb\\
\hline
cc$\alpha_1$\\
\hline
\end{tabular}
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government o
Yes. However reshape2 is a retired package. The author recommends to use
his new package tidyr.
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie
You are looking for tidyr::pivot_longer()
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics &
effect as setting its coefficient to zero for that set of
observations.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg /
Don't use the cut() function.
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkel...
Dear Catalin,
use scale_fill_gradient() and set fixed limits
ggplot(df1, aes(x=as.factor(spei), y=as.factor(month), fill = cut(cor,
zCuts))) +
geom_tile() +
scale_fill_gradient(limits = c(-0.7, 0.7))
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid
Dear Luigi,
This is rather an RStudio problem than an R problem. I suggest contacting
RStudio or their community help forum at https://community.rstudio.com/
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN
Dear Ben,
I think that you first need to go to your project and then start Rscript
from that location. renv() needs to pick up the .Renviron file located at
the root of your project.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
Dear Ding,
It seems that you are looking for the ifelse() function. Clear use of
pmax() and pmin() reduces the number of if statements.
m1 <- c(12, 23, 22, 23)
m2 <- c(23, 23, 3, 5)
Ravg <- ifelse(
pmax(m1, m2) == 23,
pmin(m1, m2),
(m1 + m2) / 2
)
Best regards,
ir. Thierry
a better understanding of power calculation by doing such exercise.
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics &
o default
df is a data.frame, id_column a string, all functions are imported.
Can someone explain to me why I'm getting this error?
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITU
0265
1.4471 2.0243 1.4092
Precision for subject_T (component 2) 1.3545 0.2436 0.9350
1.3345 1.8913 1.2962
Rho1:2 for subject_T 0.9176 0.0236 0.8631
0.9205 0.9551 0.9261
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid /
atrix(correl, ncol = length(lambda), nrow = length(lambda))
diag(sigma) <- 1
binorm <- rmvnorm(n, sigma = sigma)
bip <- apply(binorm, 2, pnorm)
bipois <- sapply(
seq_along(lambda),
function(i) {
qpois(bip[, i], lambda = lambda[i])
}
)
plot(bipois)
table(data.frame(bipois))
Be
Dear Patrick,
This is not easy to debug without a reprex
I would check the content of zzz and wide.i in the loop
str(wide.i)
zzz <- rbind(zzz, wide.i)
str(zzz)
Note that the Rmd always runs in a clean environment. This might explain
the difference
Best regards,
ir. Thierry Onkel
3)]
)
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkel...@inbo.be
ed = {d1 %>%
rownames_to_column("ID") %>%
mutate(test1 = NA, test2 = NA, test4 = NA, test5 = NA) %>%
ddply("ID",
within,
if (gender == "f" & workshop == 1) {
test1 <- 1
test1 <- 6 + test1
test2 <-
Dear Kepler,
Yes, R can do this all. But this is is to help you when you get stuck, not
to do all the work for you... You are asking basic stuff, so any
introduction book on R should contain sufficient information to get you
going. So please do read on of those first.
Best regards,
ir. Thierry
d <- paste(rmd, collapse = "\n")
cat(rmd)
```
```{r results = "asis"}
rendered <- knit(text = rmd, quiet = TRUE)
cat(rendered, sep = "\n")
```
The child.Rmd file
## ID {{x}}
```{r, fig.cap = "The caption: ID = {{x}}", echo = FALSE}
i <- {{x}}
detail
Dear Bogdan,
You are looking for x$intersectA <- vector("list", nrow(x))
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie &am
(when knitr is not loaded).
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thier
Dear Anonymous,
Please do read the help file:
https://ggplot2.tidyverse.org/reference/sec_axis.html If you read it
carefully you'll understand that is doesn't pick a time series.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT
Dear Laura,
I came across the anipaths package
(https://cran.r-project.org/web/packages/anipaths/vignettes/anipaths.html)
It might be useful for you.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK
Dear Laura,
It looks like you want to remove all rows for which each column is NA.
You can to that with the code below.
na.matrix <- is.na(MyData)
all.na.row <- apply(na.matrix, 1, all)
MyData[!all.na.row, ]
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Ov
able_B, by = "Email")
anti_join(Table_B, Table_A, by = "Email")
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kw
Dear Roberto,
The easiest way IMHO is to convert your script into an R markdown
document. See https://rmarkdown.rstudio.com/
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE
. And you
significantly reduce the need to copy/paste results.
Think about a list of packages which you can recommend to your
audience. I would consider the tidyverse collection.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT
. Here is some pseudo code.
my_summary <- function(input) {
raw <- read.table(input)
summarised <- summary(raw)
output <- calculate_output(input)
write.csv(summarised, output)
}
inputs <- list.files("raw/data/path")
sapply(inputs, my_summary)
Best regar
Try to (re-)install magrittr.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality A
1] drat_0.1.3 bit_1.1-12 odbc_1.1.2 compiler_3.4.3 hms_0.3
tools_3.4.3pillar_1.2.1 tibble_1.4.2
[9] yaml_2.1.17Rcpp_0.12.14 bit64_0.9-7blob_1.1.0
rlang_0.2.0fortunes_1.5-4
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
I
This is described in R FAQ 7.31
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thier
Dear Paula,
There are probably missing observations in your data set. Read the
na.action part of the glm help file. na.exclude is most likely what you are
looking for.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR
The maximum over twelve columns is the maximum of the twelve maxima of
each of the columns.
single_col_max <- apply(x, 2, max)
twelve_col_max <- apply(
matrix(single_col_max, nrow = 12),
2,
max
)
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Fl
Dear Sanjeev,
It seems that you system neither supports X11 devices nor cairo
devices. See http://lmgtfy.com/?q=R+unable+to+open+connection+to+X11
for possible solutions.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR
Dear Lenny,
\beta_1 is the log odds ratio for age. If you want the odds ratio,
then you need to calculate it.
It looks like some reading up on glm won't harm you.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR
Dear Lenny,
You can do this by using Age as an offset factor.
dataset$wAge <- dataset$Age * 1.02
glm(cbind(Yes,No) ~ offset(wAge) + Times + Type, family=binomial, data =
dataset)
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Fland
. Note that R is case sensitive. the extension should be .RData
instead of Rdata. See
https://cran.r-project.org/doc/manuals/r-release/R-exts.html#Data-in-packages
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN
You need to make sure that the rJava package is working.
Consider using the readxl package instead of xlsx.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Slightly faster: sum(cumsum(hyd) <= .5 * sum(hyd))
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Bio
Dear Elahe,
Something like
joint <- rbind(
data.frame(x = gg$Az, veg = gg$veg, type = "Alz"),
data.frame(x = tt$Cont, veg = gg$veg, type = "Cont")
)
ggplot(joint, aes(x = x, fill = veg, colour = type)) + geom_plot(alpha = 0.2)
Best regards,
ir. Thierry Onkelinx
Sta
Dear Larry,
Have a look at https://github.com/inbo/rstable That is a dockerfile
with a stable version of R and a set of packages.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE
Hi anonymous,
?prop.test states that it returns a list. And one of the element is
'p.value'. str() on the output of prop.test() reveals that too. So
prop.test()$p.value or prop.test()["p.value"] should work.
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaams
wx), ylim = 0:1)
Best regards,
Thierry
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
t
Dear Massimo,
It seems straightforward to use weighted.mean() in a dplyr context
library(dplyr)
mydf %>%
group_by(date_time, type) %>%
summarise(vel = weighted.mean(speed, n_vehicles))
Best regards,
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Gove
The combination of list.files(), gsub() and file.rename() should to the
trick.
ir. Thierry Onkelinx
Statisticus/ Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg /
Dear Axel,
I've used environment for such problems.
assign("xs", xs, envir = my.env) in the myApp function
get("xs", envir = my.env) in the server function
Best regards,
ir. Thierry Onkelinx
Statisticus/ Statiscian
Vlaamse Overheid / Government of Flanders
INSTI
Dear Paul,
We install R in C:/R/R-x.y.z and packages in C:/R/library. This makes
the packages location independent from the R version.
Best regards,
ir. Thierry Onkelinx
Statisticus/ Statiscian
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH
. Thierry Onkelinx
Statisticus/ Statiscian
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkel...@inbo.be
Kliniekstraat 25, B-1070
Dear Axel,
I tend to place Shiny apps in the "inst" directory of the package. See
https://stackoverflow.com/questions/37830819/developing-shiny-app-as-a-package-and-deploying-it-to-shiny-server
Best regards,
ir. Thierry Onkelinx
Statisticus/ Statiscian
Vlaamse Overheid / Government o
from https://github.com/inbo/inbomd_examples.
Note that you need some extra work after installing INBOmd to
inbo_rapport() to run. See the README at https://github.com/inbo/INBOmd
I've created an issue https://github.com/rstudio/rmarkdown/issues/1138
ir. Thierry Onkelinx
Instituut voor natuur- en
nning the
post_processor manually works.
eval(parse(
text = readLines(
"
https://raw.githubusercontent.com/inbo/INBOmd/post_processor/R/rsos_article.R
"
)[72:92]
))
post_processor(output_file = "skeleton.tex")
system("pdflatex skeleton.tex")
Best regards,
i
Dear Heinz,
Yes. The idea of the post_processor() is that 1) pandoc converts the .md to
.tex 2) the post_processors changes the .tex 3) the .tex is compiled into
.pdf Hence the post_processors need to read, change and overwrite the tex
output file.
Best regards,
ir. Thierry Onkelinx
Instituut
width = 60,
concordance = TRUE
),
opts_chunk = opts_chunk,
knit_hooks = knit_hooks
),
pandoc = pandoc_options(
to = "latex",
latex_engine = "xelatex",
args = args,
keep_tex = keep_tex
),
post_processor = post_processor,
of
observation per group is useful too.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the stat
01 909.9946 939.6379 2476.415 100 a
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the stati
library(dplyr)
library(lubridate)
data %>%
group_by(floor_date(Timestamp, unit = "day")) %>%
summarise(rain = sum(Rain_mm_tot))
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team
Dear Greg,
Make sure that your x variable (Betas) is categorical. That is required for
geom_boxplot().
And please do read the posting guide.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteits
UE/FALSE against unknown hence the
output is unknown.
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the statistic
other
situations it might be more of an issue.
The workaround (NA -> FALSE, basically) is in place in R-patched and
R-devel.
-pd
> On 28 Apr 2017, at 07:47 , Thierry Onkelinx <thierry.onkel...@inbo.be>
wrote:
>
> We have several computers with the same problem.
>
> Op 28
We have several computers with the same problem.
Op 28 apr. 2017 7:25 a.m. schreef "Jean-Claude Arbaut" :
Hello,
I am currently getting a strange error when I call installed.packages():
Error in if (file.exists(dest) && file.mtime(dest) > file.mtime(lib) && :
missing
Dear Mustafa,
Please keep the mailing list in cc.
Since you claim to have written the code, you can share the code so we can
review it. That makes more sense than having us to write code for you...
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute
combination
3. select the relevant drugs in sheet 2 with filter()
4. join long sheet 1 and filtered sheet2 with inner_join()
5. summarise() the drug codes and names after group_by(patient_id)
6. count() the number of drug codes.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
Please don't cross post. You've send the message to the mixed models
mailing list as well (which more appropriate).
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality A
)
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the statistician after the experiment is done
, XML, JSON,
... will depend upon the data (and the metadata).
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
ry(leaflet)
leaflet() %>%
addProviderTiles(
"Thunderforest.OpenCycleMap",
options = providerTileOptions(apikey = Sys.getenv("OCM_API"))
)
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
team
Dear Katherina,
Multcomp can't handle interactions automatically. You need to create the
contrasts manually.
Best regards,
Thierry
Op 25-mrt.-2017 08:13 schreef "Katharina Voigt" :
> Hi,
> I want to obtain post hoc comparisons for a model with a three-way
>
could use the boot package as Bert
suggested.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the stat
Dear Karl,
This is hard to investigate without a reproducible example.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 An
Dear Petr,
Don't use xlim() but rather coord_cartesian(xlim = ...). See
https://rpubs.com/INBOstats/zoom_in
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality A
Dear all,
Thanks to Ista and Olivier. The solution of Ista works for some characters
but not all. The solution of Olivier works, at least for the characters
that I've tried.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team
mand gives several similar warnings, all related to the symbols
which are not rendered properly:
Warning messages:
1: In grid.Call.graphics(L_text, as.graphicsAnnot(x$label), ... :
conversion failure on '' in 'mbcsToSbcs': dot substituted for
I'm running R 3.3.2 under Ubuntu 16.04.1 and ggplot
able(region = prefix$region))
)
system.time({
prefix.sample <- sample(prefix$prefix, n, prob = prefix$Freq, replace =
TRUE)
nums <- apply(
matrix(
sample(0:9, 6 * n, replace = TRUE),
ncol = 6
),
1,
paste,
collapse = ""
)
phonenumbers <- pas
e", Shore = "red"))
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the statistician
Dear Rui,
nlme is a recommended package, lme4 is (currently) not. You need to install
it.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Klinieks
Dear Luanna,
Assuming that oldnames and newnames are character (and not factor), the
just use stringsAsFactors = FALSE. That will save you from having to
convert the factors back to character.
data.frame(oldnames, newnames, stringsAsFactor = FALSE)
Best regards,
ir. Thierry Onkelinx
Instituut
t;, "Xvalue", XA:XB) %>%
gather("Ycat", "Yvalue", YA:YB)
# create the plot
library(ggplot2)
ggplot(long, aes(x = Xvalue, y = Yvalue)) +
geom_smooth(method = "lm") +
geom_point() +
facet_grid(Ycat ~ Xcat, scales = "free")
Best regards,
Dear Duncan,
I'd recommend to switch from Sweave to knitr. Knitr has more options for
handling warnings and errors than Sweave.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biomet
Dear Marna,
It's a combinations of two functions: %*% and t()
help("%*%") and help("t") will open their helpfiles.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / t
Here is a solution
ggplot(exdatframe2) +
geom_tile(aes(x = exdatframeT, y = Name, fill = knownstate), colour =
"black", height = 0.5) +
scale_fill_discrete(na.value = "white")
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research
b
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the statistician after the experiment is do
Dear Da,
NA represents an unknown value x. 1 ^ x = 1 for all possible values of x.
Hence 1 ^ NA = 1.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality A
the author, license and version at the package level.
devtools and Roxygen make it very easy to create a package. Even if it
would contain only one or a few functions.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie
Dear Luis,
Please don't post in HTML, it mangles the code.
You want something like
p + scale_shape_manual(values = c(16, 2))
Untested as you failed to provide a reproducible example.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
Dear Roger,
Maybe you want to return(mod) instead of return(mod$coef)
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 An
Here is a ggplot2, tidyr, dplyr solution
library(tidyr)
library(dplyr)
library(ggplot2)
ds %>%
gather() %>%
group_by(key) %>%
summarize(total = sum(value)) %>%
ggplot(aes(x = key, y = total)) +
geom_bar(stat = "identity")
ir. Thierry Onkelinx
Instituut voor n
Dear Anonymous,
It's seems like that package never made it to CRAN. You should contact the
package author or the author of the reference.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg /
Dear Benjamin,
Have a look at FAQ 2.11:
https://cran.r-project.org/doc/FAQ/R-FAQ.html#Can-I-use-R-for-commercial-purposes_003f
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biomet
Dear Stephen,
I use https://zenodo.org/ to get a DOI for a package. E.g.
http://dx.doi.org/10.5281/zenodo.48423
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics &
a
model to only 4 points.
fit1 <- lme(value ~ time * CorT, random = ~1|SS, data = data10)
fit2 <- lme(value ~ time * CorT, random = ~time|SS, data = data10)
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Bio
of question.
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the statistician after the experiment is
A reproducible example makes your problem easier to understand.
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
6, Adjusted R-squared: 0.9624
F-statistic: 3829 on 4 and 595 DF, p-value: < 2.2e-16
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Ander
Please keep the mailing list in cc.
See http://adv-r.had.co.nz/Reproducibility.html for some instructions.
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Klinieks
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