I am using R Studio and writing code to determine p-values for statistical
t-tests. Code is below. When I print out the values in the loop for
PTMpvalMeans they are correct, but when I store them the 10th one
overwrites the 11th. Can someone tell me what I am doing wrong? Thanks in
advance, Eric
What is the best package for fitting a model where both the mean and the
variance are latent variables? I'm trying to model skew that arises from
correlation, i.e., a positive correlation between mean and variance causes
positive skew.
For example,
m ~ a_m + b_m . x + e_m
s ~ a_s + b_s . x + e_s
On 30-11-2013, at 08:37, Loyack, Eric wrote:
> I am using R Studio and writing code to determine p-values for statistical
> t-tests. Code is below. When I print out the values in the loop for
> PTMpvalMeans they are correct, but when I store them the 10th one
> overwrites the 11th. Can someon
On 13-11-30 4:37 PM, Loyack, Eric wrote:
I am using R Studio and writing code to determine p-values for statistical
t-tests. Code is below. When I print out the values in the loop for
PTMpvalMeans they are correct, but when I store them the 10th one
overwrites the 11th. Can someone tell me wha
On 11/30/2013 07:05 AM, Jacquelyn Pless wrote:
Hi all,
I am attempting to create a weights object and perform a Moran I test as
well. I have a very large spatial weights matrix (roughly 22,000x22,000)
that was created in Excel and read into R, and I'm now trying to implement:
library(spdep)
SW=
Hi,I am trying to port the Matlab code in the link below to R:
http://en.literateprograms.org/Asian_Option_Pricing_(MATLAB)This code solves a
PDE with initial and boundary conditions.Could anyone point me in the right
direction in terms of what packages I should use ?Best Regards,Tom
Dear R Users,
I wish to estimate a regression:
y=a+b x1+c x2+d x3+e
where a is the constant, b,c,d are coefficients and e represents the
residuals. However, I find x1 and x2 to correlate. In order to avoid
multicollinearity, I split up the estimation:
(1) x2~a1+ b1 x1 + e1
(2) y=a2+b2 x1+ c2 e1+
On 30-11-2013, at 11:42, Tom O'Brien wrote:
> Hi,I am trying to port the Matlab code in the link below to R:
> http://en.literateprograms.org/Asian_Option_Pricing_(MATLAB)This code solves
> a PDE with initial and boundary conditions.Could anyone point me in the right
> direction in terms of w
Hi,
Thanks for reply!
Three things:
1.
I did not write that some of the data has more then 31 NA in the column and
then it is not possible to run lm()
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
0 (non-NA) cases
In this case program should return "NA" symbol and go
On Nov 30, 2013, at 1:43 AM, Jim Lemon wrote:
> On 11/30/2013 07:05 AM, Jacquelyn Pless wrote:
>> Hi all,
>>
>> I am attempting to create a weights object and perform a Moran I test as
>> well. I have a very large spatial weights matrix (roughly 22,000x22,000)
>> that was created in Excel and re
Hi,
#1 & 2:
set.seed(432)
dat1 <- as.data.frame(matrix(sample(c(1:60,NA),154*337,replace=TRUE),ncol=337))
colnames(dat1) <- c(paste("F",1:3,sep="."),paste("r",1:334,sep="."))
lst1 <- lapply(paste("r",1:334,sep="."),function(x)
cbind(dat1[,c(1:3)],dat1[x]))
lst2 <- lapply(lst1,function(x) {
Hi,
I was able to read the file after saving it as .csv. It seems to work without
any errors.
dat1<-read.csv("Book2.csv", header=T)
###same as previous
lst1 <- lapply(paste("r",1:334,sep="."),function(x)
cbind(dat1[,c(1:3)],dat1[x]))
lst2 <- lapply(lst1,function(x) {colnames(x)[4] <-"r";x} )
Hey!
Yes,
only the D-W test takes so much time, did not check it yet
I checked results (estimates) with manually run regressions (in excel) and
they are correct.
I only change the "width" to 31 and "each=123" to 124, cause it should be
((154-31)+1) x 334 = 41416 matrix
with the lag in D-W test I
Rob Tibshirani and I are offering a MOOC in January on Statistical Learning.
This massive open online course" is free, and is based entirely on our new book
An Introduction to Statistical Learning with Applications in R
(James, Witten, Hastie, Tibshirani 2013, Springer).
http://www-bcf.usc.edu
Hi,
No problem.
In that case, each column will be a list. For example if I take the first
element of `lst2`
dW1 <- rollapply(lst2[[1]],width=32,FUN=function(z) {z1 <- as.data.frame(z);
if(!sum(!!rowSums(is.na(z1 {l1 <-lm(r~F.1+F.2+F.3,data=z1);
durbinWatsonTest(l1,max.lag=3) } else rep(NA,
I have 4 columns: Vehicle ID, Vehicle Class, Vehicle Length and Vehicle Width.
Every vehicle has a unique vehicle ID (e.g. 2, 4, 5,...) and the data was
collected every 0.1 seconds which means that vehicle IDs are repeated in
Vehicle ID column for the number of times they were observed. There ar
Hi Arun,
Thank you very much for your kind response. Sorry for my delayed response.
Your solutions for the first two questions are quite good for my purpose.
Since nobody responded, can you please have a look at the 3rd question? It'll
be my great help, if you can give me suggestions.
Regards,
1. A nice example of why posting a small reproducible example would
help get you a useful reply. Your wordy description may not suffice.
2. You are requested not to post in HTML. This is a mailing list, not
a web application.
3. table(class$'Vehicle width') is not a function; it is a table
object
Hi,
It is better to provide a reproducible example.
May be this helps:
set.seed(252)
dat1 <- data.frame(`Vehicle ID`=sample(150,150,replace=FALSE),`Vehicle
Class`=rep(1:4,c(20,40,30,60)), `Vehicle length`=
sample(15:25,150,replace=TRUE), `Vehicle width`=
sample(4:10,150,replace=TRUE),check.names
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