On 8/2/2018 7:11 PM, cjg15 wrote:
Hi - Does anyone know what the variables CID and SID are in the
dataMultilevelIV dataset?
The example from page 18-19 of
https://cran.r-project.org/web/packages/REndo/REndo.pdf has
formula1 <- y ~ X11 + X12 + X13 + X14 + X15 + X21 + X22 + X23 + X24 + X31 +
X32
You can easily test linear restrictions using the function linearHypothesis()
from the car package.
There are several ways to set up the null hypothesis, but a straightforward one
here is:
> library(car)
> x <- rnorm(10)
> y <- x+rnorm(10)
> linearHypothesis(lm(y~x), c("(Intercept)=0", "x=1"))
Hi - Does anyone know what the variables CID and SID are in the
dataMultilevelIV dataset?
The example from page 18-19 of
https://cran.r-project.org/web/packages/REndo/REndo.pdf has
formula1 <- y ~ X11 + X12 + X13 + X14 + X15 + X21 + X22 + X23 + X24 + X31 +
X32 + X33 + (1 + X11 | CID) + (1|SID)
w
Hi Petr,
I recently had to align the minima of deceleration events to form an
aggregate "braking profile" for different locations. It seems as
though you are looking for something like:
find_increase<-function(x,surround=10) {
inc_index<-which.max(diff(x))
indices<-(inc_index-surround):(inc_inde
You may get a response here, but as this is primarily a statistical
question, not a question about R programming, so it is off topic here. I
would suggest that you post this on stats.stackexchange.com or other
statistics site instead. There is a large literature on this sort of thing .
Cheers,
Ber
Dear All,
once we run the following code, the results of the test will give us the
expected obvious, samples are from the common distribution...
library(kSamples)
u1 <- sample(rnorm(500,10,1),20,replace = TRUE)
u2 <- sample(rnorm(500,10,1),20,replace = TRUE)
u3 <- sample(rnorm(500,10,1),20,rep
Logic:
!(E == "fail" & F == "fail) <==>
(E == "pass" | F == "pass")
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Thu, Aug 2, 2018 at 8:57 AM, Sa
Given that clarification, I'd just generate the full set and remove
the ones you aren't interested in, as in:
scenarios <- expand.grid(A = c("pass", "fail"), B = c("pass", "fail"), C =
c("pass", "fail"), D = c("pass", "fail"), E = c("pass", "fail"), F =
c("pass", "fail"))
scenarios <- subset(sc
From what I can tell, the simplest way is to
First generate all the combinations
Then exclude those you don't want.
Here's an example, with only three variables (D, E, and F), that excludes those
where E and F both fail
> tmp <- c('p','f')
> X <- expand.grid(D=tmp, E=tmp, F=tmp)
> X <- sub
Thank you for pointing that out, I realize not only did I use the wrong
language but I did not describe the situation accurately. I do need to
address the situation where both variables E and F actually pass, that is
the majority case, one or the other can fail, but there can never be a
situation
R is free and open source. Your queries are inappropriate for this list,
which is about help for programming in R. Please go here and follow the
relevant links to answer your questions:
https://www.r-project.org/
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people k
Dear all
Before I start to reinvent wheel I would like to ask you if you have some easy
solution for aligning data
I have something like this
x<-1:100
set.seed(42)
y1<-c(runif(20)+1, 1.2*x[1:80]+runif(80))
y2<-c(runif(40)+1, 1.2*x[1:60]+runif(60))
plot(x,y1)
points(x,y2, col=2)
with y increase
Hello,
Thank you for replying. I am sorry te codes were not attached, I did attach
them but I think it got blocked due to some filters. I am pasting the link
for the codes:
https://github.com/zhentaoshi/convex_prog_in_econometrics/tree/master/C-Lasso/PLS_static
The authors never replied I have co
Suggest you take a look at the R website at www.r-project.org; the most
important answers are evident there.
If you 'require' more authoritative answers within a particular timescale, I
suggest you engage an R consultant and pay for them. This is a voluntary list.
S Ellison
> -Original
> On Thu, Aug 2, 2018 at 11:20 AM, R Stafford
> wrote:
> > But I have the extra condition that if E is true, then F must be false, and
> > vice versa,
Question: Does 'vice versa' mean
a) "if E is False, F must be True"
or
b) "if F is True, E must be False"?
... which are not the same.
b) (and
Dear R Project team,
I am representing the System Toxicology department of Philip Morris
International in the scope of a Windows 10 migration project.
This project is currently at the end of the assessment phase. We would require
an answer to this email by the end of this week.
I would like to
dear members,
I am using R to do my research for Day Trading in
INDIA. I have a list of 206 stocks to work with.
I have extracted a parameter of a stock based on the OHLC data of the stock. It
includes values both less than and greater than 1 ( It basically is a ratio)
This should do it:
> x <- rnorm(10)
> y <- x+rnorm(10)
> fit1 <- lm(y~x)
> fit2 <- lm(y~-1 + offset(0 + 1 * x))
> anova(fit2, fit1)
Analysis of Variance Table
Model 1: y ~ -1 + offset(0 + 1 * x)
Model 2: y ~ x
Res.Df RSS Df Sum of Sq F Pr(>F)
1 10 10.6381
Hi
Good that you have finally got desired result.
Regarding aggregate, you could consult help page
?aggregate
It has many good examples how to use it.
and for understanding factors
?factor is your friend and/or pages 16+ from R intro.
Cheers
Petr
From: Diego Avesani
Sent: Thursday, August 2
Dear Petr,
I have read the file:
MyData <- read.csv(file="obs_prec.csv",header=TRUE, sep=",")
I have used POSIXct to convert properly the date
MyData$date2<-as.POSIXct(MyData$date, format="%m/%d/%Y %H:%M")
creating a second field inside MyDate.
I have converted the -999 to NA:
MyData[MyData== -
Hi,
I try to run the regression
y = beta_0 + beta_1 x
and test H_0: (beta_0, beta_1) =(0,1) against H_1: H_0 is false
I believe I can run the regression
(y-x) = beta_0 +beta_1‘ x
and do the regular F-test (using lm functio) where the hypothesized
coefficients are all zero.
Is
Hi Saptorshee,
Two comments:
1. no attachments made it through to the list. You probably need to include
the code directly in your email, and send your email as plain text
(otherwise information gets stripped)
2. for anyone interested in following up on Saptorshee's question, I
searched for the pap
Dear PIKAL, Dear all,
thanks again a lot.
I have finally understood what "in line" means.
I would definitely read some "R-intro" and in this moment I am reading a
R-tutorial.
I would not post formatted messages.
I would ask if it is possible to have some final suggestions:
- how to have daily mea
Well,
you followed my advice only partly. Did you get rid of your silly -999 values
before averaging? Probably not.
Did you tried aggregating by slightly longer construction
aggregate(test[,-1], list(format(test$date, "%Y-%m-%d")), mean)
which keeps difference in month and year? Probably not.
We
Dear all,
I have found and error in the date conversion. Now it looks like:
MyData <- read.csv(file="obs_prec.csv",header=TRUE, sep=",")
# change date to real
MyData$date<-as.POSIXct(MyData$date, format="%*m*/%*d*/%Y %H:%M")
After that I apply the PIKAL's suggestions:
aggregate(MyData[,-1], lis
Hi
see in line (and please do not post HTML formated messages, it could be
scrammbled)
From: Diego Avesani
Sent: Thursday, August 2, 2018 8:56 AM
To: jim holtman ; PIKAL Petr
Cc: R mailing list
Subject: Re: [R] read txt file - date - no space
Dear
I have check the one of the line that gives
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