Hello everyone,
I have a question regarding simulating based on runif. Let say I have
generated matrix A and B based on runif. Then I find mean for each matrix A and
matrix B. I want this process to be done let say 10 times. Anyone can help me.
Actually I want make the function that I can pla
Gentlemen,
Thank you so much for your help. You have solved my problem.
> Using Achim's d this also works to generate z where FUN is a function used
> to transform the index column and format is also passed to FUN.
>
> z <- read.zoo(d, index = "time", FUN = as.yearqtr, format = "Q%q %Y")
>
> On S
On 1/27/2018 12:16 PM, David Winsemius wrote:
John (to a serial querulant):
...but with such a sweeping lack of
information from you, don't congratulate yourself if you get a helpful
answer. It wasn't your fault.
David Winsemius
Alameda, CA, USA
Second that nomination!
'Any technolog
I assume you are using the qcc package's qcc function.
example(qcc) gives an example of adding abline's to its plot:
# add warning limits at 2 std. deviations
q <- qcc(diameter[1:25,], type="xbar", newdata=diameter[26:40,],
plot=FALSE)
(warn.limits <- limits.xbar(q$center, q$std.dev, q$sizes,
A) Without your data, it is very difficult to see what your problem is. You
need to include both data and code to create a reproducible example. [1][2][3]
B) Please follow the guidance in the Posting Guide mentioned in the footer of
every message on this list; in particular note that this is a p
Hello useRs,
A new package, IndexNumR, has been released on CRAN.
IndexNumR provides a set of functions for computing various bilateral and
multilateral indices. It is designed to compute price or quantity indices over
time. Bilateral indices include Laspeyres, Paasche, Fisher, Tornqvist,
Sato
Hello everybody out there using R,
When putting multiple plots with thousands of data points into a single PDF
file, this file can get huge and take a long time to open.
The following post describes exactly the same problem in Matplotlib, as well as
a nice fix for it: Matplotlib: multipage PD
Dear all,
The latest issue of The R Journal is now available at:
https://journal.r-project.org/archive/2017-2/.
New this time - quick access to news and notes 2013-to date in the
navigation bar to the left including new Forwards and R-teaching columns;
articles in 2017-2 may link to code and
Hello,
I believe the following is simpler.
It changes the OP's code a bit and uses lapply, not apply.
res2 <- lapply(C, fitdist, "gamma")
do.call(rbind, lapply(res2, `[[`, "estimate"))
# shape rate
#A 3.702253 1.234126
#B 31.300800 3.912649
Hope this helps,
Rui Barradas
On 1/29/20
Capture the results of the apply command into an object and then work with
that. Here is one way to do it:
> res <- apply(C, 2, fitdist, "gamma")
> out <- c( res$A$estimate["shape"], res$B$estimate["shape"],
res$A$estimate["rate"], res$B$estimate["rate"])
> names(out) <- c("A shape","B shape","A r
Hi,
Let say I have data by two columns A and B, and I have fit each column using
the gamma distribution by 'fitdist' . I just want the result show only the
shape and rate only.
Eg:
library(fitdistrplus)
A <-c(1,2,3,4,5)
B<-c(6,7,8,9,10)
C <-cbind(A,B)
apply(C, 2, fitdist, "gamma")
Output sho
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