Dear R users,
I'd like to remove some descriptions when I use "filter".
> filter(1:10, rep(1, 3))
Time Series:
Start = 1
End = 10
Frequency = 1
[1] NA 6 9 12 15 18 21 24 27 NA
That is, I want only this
[1] NA 6 9 12 15 18 21 24 27 NA
Thank you in advance.
Ka
quot; are too big.
So, my question is that
Is there any better idea to avoid "for" statement for this problem?
Thank you in advance.
Kathie
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=5) -> 2
sum(y==6) -> 1
However, in one computation I want to get this vector [1,2,0,3,0,2,1].
Thank you in advance.
Kathie
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Dear R users
When I use OPTIMX with BFGS, I've got the following error message.
-
> optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS")
Error: Gradient function might be wrong - check it!
Dear R users
When I use OPTIM with BFGS, I've got a significant result without an error
message. However, when I use OPTIMX with BFGS( or spg), I've got the
following an error message.
> optim
To be honest,
The first derivative of my objective function is very complicated so I
ignore this. Could it lead to this sort of problem?
Kathie
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Dear R users
I am trying to use OPTIMX(OPTIM) for nonlinear optimization.
There is no error in my code but the results are so weird (see below).
When I ran via OPTIM, the results are that
Initial values are that theta0 = 0.6 1.6 0.6 1.6 0.7. (In fact true vales
are 0.5,1.0,0.8,1.2, 0.6.)
--
almost forgot. In fact, I want to generate correlated Poisson random vectors.
Thank you anyway
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Dear R users
I'd like to generate two sets of random numbers with a fixed correlation
coefficient, say .4, using R.
Any suggestion will be greatly appreciated.
Regards,
Kathryn Lord
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I understood that the "function" has to be vectorized.
I was just wondering which one is faster.
Thanks
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Thanks a lot all of you
Yes, you're right.
However, as i know, "do.call" calls its function once, but "apply(or sapply
etc)" not. So, I think do.call is faster than apply. That's why i am trying
to use do.call.
Am I right??
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Dear all,
Even though one of R users answered my question, I cannot understand, so I
re-ask this question.
I am trying to use "do.call", but I don't think I totally understand this
function.
Here is an simple example.
> B <- matrix(c(.5,.1,.2,.3),2,
Dear all,
I am trying to use "do.call", but I don't think I totally understand this
function.
Here is an simple example.
> B <- matrix(c(.5,.1,.2,.3),2,2)
> B
[,1] [,2]
[1,] 0.5 0.2
[2,] 0.1 0.3
> x <- c(.1,.2)
> X <- cbind(1,x)
> X
Hi, R users,
Here is an example.
k <- c(1,2,3,4,5)
i <- c(0,1,3,2,1)
if k=1, then j=0 from i
if k=2, then j=0, 1 from i
if k=3, then j=0, 1, 2, 3 from i
if k=4, then j=0, 1, 2 from i
if k=5, then j=0, 1 from i
so i'd like to create a list like below.
> list
k j
1 1 0
2 2 0
3 2 1
4 3 0
5
Hi, R users,
Here is an example.
k <- c(1,2,3,4,5)
i <- c(0,1,3,2,1)
if k=1, then i=0
if k=2, then i=0, 1
if k=3, then i=0, 1, 2, 3
if k=4, then i=0, 1, 2
if k=5, then i=0, 1
so i'd like to create a list like below.
> list
k i
1 1 0
2 2 0
3 2 1
4 3 0
5 3 1
6 3 2
7 3 3
8 4 0
9 4 1
1
Dear R users,
I have two n*1 integer vectors, y1 and y2, where n is very very large.
I'd like to compute
elbp = 4^(y1) * 5^(y2) * sum_{i=0}^{max(y1, y2)} [{ (y1-i)! * (i)! *
(y2-i)! }^(-1)];
that is, I need to compute "elbp" for each (y1, y2) pair.
So I made R code like below, but I don't t
Dear R users,
Would you plz tell me how to avoid this "for" loop blow??
I think there might be a better way to reduce running time.
--
## y1 and y2 are n*1 vectors
for (k in 1:n){
thanks a lot.
good day.
Kathie
On Fri, Apr 16, 2010 at 1:43 PM, Henrique Dallazuanna [via R] <
ml-node+2013302-929204043-67...@n4.nabble.com
> wrote:
> Try this:
>
> sweep(a, 1, b, '/')
>
> On Fri, Apr 16, 2010 at 2:30 PM, Kathie <[hidden
> email]<
Dear R users,
I am looking for more efficient way to compute the followings
--
a <- matrix(c(1,1,1,1,2,2,2,2),4,2)
b <- matrix(c(1,2,3,4),4,1)
Eventually, I want to get this matrix, `c`.
c <- matrix(c(1/1,1/2,1/3,1/4,2/1,
Dear R users,
I need some advises on how to use R to optimize this function with the
following constraints.
f(x1,x2,x3,y1,y2,y3,)
= gamma(x1+x2-1)/{gamma(x1)*gamma(x2)} * y1^(x2-1) * y2^(x1-1)
+ gamma(x1+x3-1)/{gamma(x1)*gamma(x3)} * y1^(x3-1) * y3^(x1-1)
+ gamma(x2+x3-1)/{gamma(x2)*gamma(x3)
Dear R users,
I need some advises on how to use R to optimize a nonlinear function with
the following constraints.
f(x1,x2,x3,x4,x5,x6)
s.t
0 < x1 < 1
0 < x2 < 1
0 < x1+x2 < 1
-inf < x3 < inf
-inf < x4 < inf
0 < x5 < inf
0 < x6 < inf
Is there any built-in function or something for these co
Dear R users,
is there way to ignore an error and go back to 1st line?
I mean,
#---
while (or repeat)
{
1
2
.
.
.
6
}
#-
For example, if I have an error in the 6th line, the
ason "Reduce" doesn't work is that it has multi-dimentional
list..
Gabor Grothendieck wrote:
>
> See this:
>
> https://stat.ethz.ch/pipermail/r-help/2009-August/208002.html
>
> On Sat, Aug 22, 2009 at 11:41 AM, kathie
> wr
Dear R users,
I have the list as follows;
#--
> z
[[1]]
[[1]][[1]]
matrix(A)
[[1]][[2]]
matrix(B)
[[1]][[3]]
matrix(C)
[[2]]
[[2]][[1]]
matrix(D)
[[2]][[2]]
matrix(E)
[[2]][[3]]
matrix(F)
#-
Dear R users,
I try to compute this summation,
http://www.nabble.com/file/p25054272/dd.jpg
where
f(y|x) = Negative Binomial(y, mu=exp(x' beta), size=1/alp)
http://www.nabble.com/file/p25054272/aa.jpg
http://www.nabble.com/file/p25054272/cc.jpg
In fact, I tried to use "do.call" function
Dear R users...
I have a list, "z", below.
z<-list(matrix(c(11,11,9,0,0,0),3,2),matrix(c(10,10,10,1,1,1),3,2),
matrix(c(7,10,1,1),2,2))
> z
[[1]]
[,1] [,2]
[1,] 110
[2,] 110
[3,]90
[[2]]
[,1] [,2]
[1,] 101
[2,] 101
[3,] 101
[[3]]
Dear R users...
I'd like to change this character vector, "zz",
zz <- c("12","56","89")
to the following numeric matrix.
[,1] [,2]
[1,]12
[2,]56
[3,]89
Actually, "zz" vector has a long length.
Any comments will be greatly appreciated.
Kathryn Lord
--
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Dear R users...
I need to split this matrix(or dataframe), for example,
z <- matrix(c(13,1,1,1,1,12,0,0,0,0,8,1,0,1,1,8,0,1,0,0,
10,1,1,1,1,3,0,1,0,0,3,1,0,1,1,6,1,1,1,1),8,5,byrow = T)
> z
[,1] [,2] [,3] [,4] [,5]
[1,] 131111
[2,] 12000
Dear R users,
>From the code below, I try to compute "y" value. (In fact, y looks like a
trapezoid)
--
x <- seq(0,1,.01)
y <- ifelse(abs(x-.5)<=0.3,0,
ifelse(abs(w-.5)>=0.4,-1,
ifelse((0.1 x
[1] 0
Dear R users...
I need to change the S+ code below to R code.
I am wondering if there is a R statement equivalent for "assign" statement
in S-plus.
prime <- function(x)
{
1*(abs(x) < chuber)
}
assign("prime",prime,frame=
Dear R users...
I made this by help of one of R users.
_
X=matrix(seq(1,4), 2 , 2)
B=matrix(c(0.6,1.0,2.5,1.5) , 2 , 2)
func <- function(i,y0,j) { y0*exp(X[i,]%*%B[,j]) }
list1 <- expand.grid( i=c(1,2) , y0=c(1,2) , j=c(1,2) )
resu
Dear R users...
I made the R-code for this triple summation computation
http://www.nabble.com/file/p20517134/a.jpg
-
Here is my code..
x=seq(.1,1,.1); l=10
y=seq(1,10); m=10
z=seq(.1,1,.1); n=10
sum(sapply(1:l, function(i) {sum(sapply(1:m,
Dear R users,
I'd like to make this data
rem.y = c(-1,0,2,4,5)
from
y = c(-1,-1,0,2,2,2,2,4,4,5,5,5,5,5).
That is, I need to remove repeated values.
Here is my code, but I don't think it is efficient. How could I improve
this?
#---
Dear all
When I used the method, L-BFGS-B, in OPTIM, I've got the following message.
-
$par
[1] 0.176166426835580
$value
[1] 1322.17600079332
$counts
function gradient
88
$convergence
[1] 0
$message
[1] "CON
Dear R users...
I made the R-code for this double summation computation
http://www.nabble.com/file/p19213599/doublesum.jpg
-
Here is my code..
sum(sapply(1:m, function(k){sum(sapply(1:m,
function(j){x[k]*x[j]*dnorm((mu[j]+mu[k])/sqrt(sig[k]+si
Dear R users...
I made the R-code for this double summation computation
http://www.nabble.com/file/p19213463/doublesum.jpg
-
Here is my code..
sum(sapply(1:m, function(k){sum(sapply(1:m,
function(j){x[k]*x[j]*dnorm((mu[j]+mu[k])/sqrt(sig[k]+sig
Dear R users,
When I use two functions, 'optim' and 'integrate', simultaneously, I always
get an error like this
--
numint = function(z) {
dlnorm(z,mu[1],sqrt(exp(g[1]))) *
dnorm((z-mu[2])/sqrt(exp(g[2])))/sqrt(exp(g
Dear R users,
I have 32 observations in data x. After sorting this, I want to compute
means and variances of 3 groups divided by "nr".
Actually, the number of groups is flexible. Any suggestion will be greatly
appreciated.
Kathryn Lord
--
;optimMLE' that would automate
> some of this and package it with common 'methods' that would assume that
> sum(fn(...)) was either a log(likelihood) or the negative of a
> log(likelihood), etc. However, before I do, I need to make more
> progress on some of my oth
Dear R users,
I used to "OPTIM" to minimize the obj. function below. Even though I used
the true parameter values as initial values, the results are not very good.
How could I improve my results? Any suggestion will be greatly appreciated.
Regards,
Kathryn Lord
#
Dear R users,
I am trying to figure out the control parameter in "optim," especially,
"fnscale" and "parscale."
In the R docu.,
--
fnscale
An overall scaling to be applied to the value of fn and gr during
optimization. If negative, turns
Dear all,
I want to min "integrate( (p1*dnorm+p2*dnorm+p3*dnorm)^(1.3))" for p, mu,
and sigma.
So, I have to estimate 8 parameters(p3=1-p1-p2).
Sometimes I got some results, but it was bad, sometimes, I got this
warning-"Error in integrate(numint, lower = -Inf, upper = Inf) : non-finite
functio
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