I made no attempt to examine your details for problems, but in general,
My problem
> is that the results change a lot depending on the initial values... I can't
> see what I am doing wrong...
>
> This is a symptom of an overparameterized model: The parameter estimates
> are unstable even though t
Dear R users,
I'im trying to find the parameters of a dynamic biomass model using maximum
likelihood estimation. I used two approaches, one by hand, with optim()
function and the other using mle2() function from package bbmle. My problem
is that the results change a lot depending on the initial va
On Oct 15, 2015, at 4:51 AM, Bhawana Sahu wrote:
> I am using R in my project for analysis of data, and I have generated SVM
> model using kernlab package with the dataset (3000 rows and 281 columns).
> Now I want to generate this model for dataset containing 8000 rows and 281
> column, but here
>From R prompt, input:
memory.limit()
which returns the amount of memory available to R.
Then, before allocating that vector, run:
library(pryr)
mem_used()
To see current memory in use.
Should be: memory.limit() - mem_used() >= 2.4GBytes
--
GG
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I may suggest this tutorial:
http://www.stat.berkeley.edu/~nolan/stat133/Fall05/lectures/profilingEx.html
and this discussion:
http://stackoverflow.com/questions/3650862/how-to-efficiently-use-rprof-in-r
which inspired this example:
Rprof("profile1.out", line.profiling=TRUE)
for(i in 1:10
On 15/10/2015 2:05 PM, amish azeem wrote:
> Dear R family,
> I am trying to develop a 3D Scatterplot for the following data
>> dput(fer)
> structure(c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5,
> 54.682478566783, 73.7179265155391, 56.0442812544372, 123.944575771864,
> 81.67159417
It is likely the "p" variable is not defined in your R environment.
Inside your function model.LIDR, the variable "p" is used before being
initialized
in any of the environments reachable by the search path, included the model.LIDR
function environment.
The remedy is to define and initiali
Thanks a lot for helping William. Will check the reference as well.
Sent from my iPhone
> On Oct 15, 2015, at 5:52 PM, William Dunlap wrote:
>
> Doing enumerative combinatorics with rejection methods rarely
> works well. Try mapping your problem to the problem of choosing
> m-1 items from n-1.
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