R Help -
I'm attempting to use fminsearch and it continues to give me errors. I have
a normal Rescorla Wagner function that has 2 parameters and returns total
error. for some reason fminsearch keeps saying the type of errors below,
I've put the function and data after it using dput
> sol <- fmins
R -
I would like to construct a matrix from the output of a loop that has 2
values it varies over the course of the loop creating a 20x20 matrix of
output values:
ap = logspace(-3, 0, 20)
am = logspace(-3, .7, 20)
for (ap in apList)
{
for (am in amList)
{
output = func(ap, am)
}
}
R Help -
Why is that in the results below, changing the order of the factor
(trialType2: levels - DD, SD, DS, SS) changes the estimates in the fixed
effects tests?
> tmp.dat4$trialType2 <- sort(tmp.dat4$trialType, decreasing = TRUE)
> mod2c <- lme(proportion.down ~ trialType2, data = tmp.dat4, ra
R-help -
I have this set of aggregated tables (sample data below via dput()). And I
would like to have delayValue as the column variables with the "temp"
(temp1, temp2, temp3) values as the row variables. However I would like to
have the temp variables *aggregated into single rows* so that I hav
R-help -
I'm trying to create axis breaks similar to this :
http://www.r-bloggers.com/wp-content/uploads/2010/08/bar-chart-natural-axis-split1.png
.
Is there a way to do this in R? Here's my code thus far:
structure(list(condition = structure(c(2L, 1L, 3L), .Label = c("con",
"exp", "unedit"), c
R Community -
I'm attempting to apply a softmax action selection to a probability
generated by a hidden Markov model. I'm having difficulties in how to
apply the softmax temperature parameter (beta). Here is my code thus far.
I'm thinking the sigmoid function will work but I need this function
1 5
> [7,] 1 6
> [8,] 1 7
> [9,] 0 7
> [10,] 1 8
> [11,] 0 8
> [12,] 1 9
> [13,] 1 10
> [14,] 1 11
> [15,] 1 12
> [16,] 1 13
> [17,] 0 13
>
>
> On Mon, Mar 5, 2012 at 1:51 PM, Edward Patzelt wrote:
> > I'm am trying
I'm am trying to create a vector that has a running total that adds each
time a 1 occurs. here's the code and data
c(1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 1L,
1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L,
0L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L,
R -
Does anyone know of a cubic gradient descent package? I found grad.desc()
but that only allows for a 2d function. I have 3 free parameters and thus
am looking for a 3d function.
Thank you,
--
Edward H. Patzelt
Research Assistant TRiCAM Lab
University of Minnesota Psychology/Psychiatr
A, NA, 3, NA,NA, NA, 2) ?
>
> Jean
>
> Edward Patzelt wrote on 08/22/2011 03:58:38 PM:
>
> > [image removed]
> >
> > Re: [R] Counting Elements Conditionally
> >
> > Edward Patzelt
> >
> > to:
> >
> > Jean V Adams
>
after it sees the first occurrence of 0 in FF following a transition, I want
it to ignore all further elements until the next transition.
On Mon, Aug 22, 2011 at 3:58 PM, Edward Patzelt wrote:
> Awesome, this is close, couple changes. Below is full data set for 1
> person. I want the c
)), .Names = c("Rev", "FF", "bin"), row.names = c(NA,
-125L), class = "data.frame")
On Mon, Aug 22, 2011 at 3:57 PM, Jean V Adams wrote:
>
> > Re: [R] Counting Elements Conditionally
> > Jean V Adams
> > to:
> > Edward Patzelt
&g
R -
I have 3 variables with data below. Variable "Rev" is a vector that changes
from 1 to 2, 2 to 3, etc Variable "FF" is a binary variable with 1's
and 0's. Variable "bin" is a different binary variable with 1's and 0's.
I want to calculate the number of elements:
1. Starting with the f
R-help -
This code iterates over a function with 2 free parameters to find a list of
values (which are the number of incorrect predictions for a computational
model). I want to find the values of i,e when there is the minimum number
of incorrect predictions. In other words, the value of "i" and
; >>
>> >> require(car)
>> >> foo <- function(x) {
>> >> if (any(grepl(4, x))) {
>> >>x <- recode(x, "2 = 1; 4 = 2")
>> >> }
>> >> return(x)
>> >> }
>> >>
>> >> da
tasets
> [8] methods base
>
> other attached packages:
> [1] car_2.0-9 survival_2.36-5 nnet_7.3-1 MASS_7.3-11
>
> again without issue, so I am thinking there must be something
> particular perhaps to your session going on, but it is difficult to
> say.
>
> On Mo
4165L, 4166L, 4167L,
> 4168L, 4169L, 4170L, 166L, 167L, 168L, 169L, 170L, 171L, 172L,
> 173L, 174L, 175L), class = "data.frame")
>
> Does that work for you? I am running:
>
> R Under development (unstable) (2011-07-30 r56564)
> Platform: x86_64-pc-mingw32/x64 (64-bi
t attached):
[1] cluster_1.13.3 grid_2.12.2 lattice_0.19-17 tools_2.12.2
On Mon, Aug 8, 2011 at 10:43 AM, Joshua Wiley wrote:
> On Mon, Aug 8, 2011 at 8:23 AM, Edward Patzelt wrote:
> > Thanks Josh for the code to post I have been trying to figure out how to
> do
> > that. Your cod
unction(x) {
if (any(grepl(4, x))) {
x <- recode(x, "2 = 1; 4 = 2")
}
return(x)
}
## do it
dat$test <- with(dat, *ave*(Slide1_RESP, Subject, FUN = foo))
On Fri, Aug 5, 2011 at 4:56 PM, Joshua Wiley wrote:
> On Fri, Aug 5, 2011 at 2:34 PM, Edward Patzelt wrote:
> >
resumably it is clearer with data.
> In any event, look at ?ifelse it is something like a vectorized if
> statement and is, I believe, preferable to your use of a for loop. I
> can probably give you a runnable solution if you can give the first
> few rows of the relevant data.
>
&
I want to write code that says "If you find an element equal to 4 in this
vector for each person in the data set tested separately, then put in 1 for
2 and 2 for 4, else leave the variable as is"
u.ppl <- (unique(init.dat1$grid))
l.ppl <- length(u.ppl)
for (i in 1:l.ppl)
{
R Community -
I am attempting to fit a model as described in Hampton, Bossaerts, and
O'doherty (J. Neuroscience) 2006. They use a bayesian hidden markov model
to model the Reversal Learning data. I have tried using HMM and depmixS4
with no success. My data is a Reversal Learning Task in which t
-
On Tue, Jun 28, 2011 at 1:27 PM, David Winsemius wrote:
>
> On Jun 28, 2011, at 1:44 PM, Edward Patzelt wrote:
>
> R help -
>>
>> I am attempting to write a script that has multiple subjects in 1 data
>> file.
>> Each subject has multiple rows with colum
R help -
I am attempting to write a script that has multiple subjects in 1 data file.
Each subject has multiple rows with columns as variables. Here is my code,
I am having problem executing it on each unique subject id (dat$Subject).
getwd()
setwd("/Users/edwardpatzelt/Desktop/Neuroimaging
f.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of
> data.
> ~ John Tukey
>
>
&g
Everyone -
What do the NaN's mean here? Is this analysis a problem?
Linear mixed-effects model fit by maximum likelihood
Data: tmp.dat
AIC BIClogLik
1611.251 1638.363 -797.6253
Random effects:
Formula: ~1 | group_id
(Intercept) Residual
StdDev: 0.0003077668 9.23671
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