Displaying 20 results from an estimated 275 matches for "decay".
2011 Feb 15
1
Passing Arguments in a function
Hi All,
I'm having some trouble assigning arguments inside a function to
produce a plot from a model
Can anyone help me? Below I've outlined the situation and examples of
failing and working code.
Regards
Mike
## data ##
decay.data <- ...
behaviors lift reach.uu estimated.conversions.uu total.reach
1 1 432.0083 770 770 0.00
2 2 432.0083 29660 29660 0.03
3 3 429.9864 30000 29850 0.03
4...
2001 Dec 14
1
nls fit to exponential decay with unknown time origin
I'm trying to use nls() to fit an exponential decay with an unknown offset
in the time (independent variable). (Perhaps this is inherently very
difficult?).
> decay.pl <- nls (amp ~ expn(b0,b1,tau,t0,t), data = decay,
+ start = c(b0=1, b1=7.5, tau=3.5, t0=0.1), trace=T)
Error in nlsModel(formula, mf, start) : singular gradi...
2004 Mar 30
1
classification with nnet: handling unequal class sizes
I hope this question is adequate for this list
I use the nnet code from V&R p. 348: The very nice and general function
CVnn2() to choose the number of hidden units and the amount of weight
decay by an inner cross-validation- with a slight modification to use it
for classification (see below).
My data has 2 classes with unequal size: 45 observations for classI and
116 obs. for classII
With CVnn2 I get the following confusion matrix (%) (average of 10
runs):
predicted
true 53 47
16 84...
2008 Dec 15
1
Population Decay in R
Hi,
I am new to R. I am trying to plot the decay of a population over time
(0-50yrs). I have the initial population value (5000) and the mortality
rate (0.26/yr) and I can't figure out how to apply this so I get a remaining
population value each year. In excel (ignoring headings) I would put 5000
in A1, in B2 I would enter the formula A1*0....
2011 Jan 15
1
Weighted least squares regression for an exponential decay function
Hello,
I have a data set of data which is best fit by an exponential decay
function. I would like to use a nonlinear weighted least squares regression.
What function should I be using?
Thank you!
[[alternative HTML version deleted]]
2007 Mar 07
0
PeriodicalUpdater with Logarithmic decay
Greetings all,
So, I''ve finally found a place to play around with the
Ajax.PeriodicalUpdater. In looking at the API, I''m liking the decay
option -- not necessarily for my current purpose, but just to keep in
mind -- and I have a question: can the decay be a function which
returns an integer? Basically, why I''m looking for is a logarithmic
decay (where the system updates a lot right after a change but then
slows down t...
2001 Dec 15
1
fit to spike with exponential decay : optim() question
...5)
spike <- function (x, t) {
b0 <- x[1]
b1 <- x[2]
tau <- x[3]
t0 <- x[4]
temp <- exp((-t+t0)/tau)
(b0 + (b1 * temp) * (t > t0))
}
spike.sos <- function (x) {
sum((amp - spike(x, t))^2)
}
guess <- c(min(amp), max(amp)-min(amp), (max(t)-min(t))/3, 0)
decay.opt <- optim(guess, spike.sos, control=list(trace=T))
xr <- (0:140)/10
plot (xr, spike(decay.opt$par, xr), type="l", col="blue")
points (t, amp)
--------
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r-help mailing list -- Read http://...
2008 Sep 25
0
Please help me interpret these results (fitting distributions to real data)
...thought of a useful metaphore for the problem I face. I am dealing
with a problem in business finance, with two kinds of related events.
However, imagine you have a known amount of carbon (so many kilograms), but
you do not know what fraction is C14 (and thus radioactive). Only the C14
will give decay events (and once that event has occurred, the atom that
decayed will never decay again). C12 will never decay. What you want to
know is a) what is the ratio of C12 to C14 at time 0, and b) how many decay
events will happen between time X and time y, or how many decay events will
happen after time...
2010 Jul 13
0
Neural Network package AMORE and a weight decay
Hi,
I want to use the neural network package AMORE and I don't find in the documentation the weight decay option.
Could someone tell if it is possible to add a regularization parameter (also known as a weight decay) to the training method.
Is it possible to alter the gradient descent rule for that?
Thanks,
Ron
_________________________________________________________________
The New B...
2004 Sep 23
0
nnet and weights: error analysis using V&R example
...{
if(verbose > 0) cat("fold ", i,"\n", sep="")
set.seed(i*i)
ri <- sample(nifold, sum(rand!=i), replace=T)
for(j in seq(along=lambda)) {
if(verbose > 10)
cat(" size =", size[j], "decay =", lambda[j], "\n")
choice[j] <- CVnn1(formula, data[rand != i,], nreps=nreps,
ri=ri, size=size[j], decay=lambda[j],
verbose=verbose, ...)
}
decay <- lambda[which.is.max(-choice)]...
2012 Oct 11
3
[LLVMdev] Question about the old C back-end
...en going through the internals of the old C back-end, I see that the
CBE encapsulates arrays into a struct. The source code has the
following comment to explain this behaviour.
// Arrays are wrapped in structs to allow them to have normal
// value semantics (avoiding the array "decay").
For example, the CBE translates:
@a = common global [10 x i32] zeroinitializer, align 16
into:
struct { unsigned int array[10]; } a;
However, the reason for this behaviour is not completely clear to me.
Can anyone give me further explanation of that is meant by 'array decay...
2004 Sep 23
0
nnet with weights parameter: odd error
...{
if(verbose > 0) cat("fold ", i,"\n", sep="")
set.seed(i*i)
ri <- sample(nifold, sum(rand!=i), replace=T)
for(j in seq(along=lambda)) {
if(verbose > 10)
cat(" size =", size[j], "decay =", lambda[j], "\n")
choice[j] <- CVnn1(formula, data[rand != i,], nreps=nreps,
ri=ri, size=size[j], decay=lambda[j],
verbose=verbose, ...)
}
decay <- lambda[which.is.max(-choice)]...
2009 Nov 09
0
Testing treatment effects on exponential decay models
Hello all:
I would like to test whether there are treatment effects on decomposition
rate, and I would like to inquire about the best, most appropriate means
using R.
I have plant decomposition data that is generally considered to follow an
exponential decay model as follows:
Wt = Wi * exp(-k * t)
Where Wt and Wi are the weights of the plant material at time t and 0,
respectively. k is a constant describing decomposition rate and is usually
reported in the literature.
Is it possible to fit a non-linear model as above and test for effects of
two, ind...
2009 Oct 27
1
Detection Times and Poisson Distribution
Dear All,
Apologies if my questions are too basic for this list.
I am given a set of data corresponding to list of detection times (real,
non-integer numbers in general) for some events, let us say nuclear
decays to fix the ideas.
It is a small dataset, corresponding to about 400 nuclear decay times.
I would like to test the hypothesis that these decay times are
Poissonian-distributed.
What is the best day of dealing with the data? Should I consider the
cumulative number of detections vs time, the time i...
2004 Jun 14
2
CVnn2 + nnet question
Hi,
I am trying to determine the number of units in the hidden layer
and the decay rate using the CVnn2 script found in MASS directory
(reference: pg 348,MASS-4).
The model that I am using is in the form of Y ~ X1 + X2 + X3...
+ X11 and the underlying data is time-series in nature.
I found the MASS and nnet package extremely useful (many thanks
to the contributors).
Howev...
2010 Dec 01
0
Multivariate time series - Poisson with delayed lags
...ble them effectively. What I am looking to
do is model my dependent variable y_t as a Poisson family function of lags
of several independent variables and lags of y_t. I would like to include
all lags up through t-n where n is specified and greater than 1, and have
the lagged values weighted by a decay factor that increases exponentially
with each time step further back in time from t. The time delay n of course
I can construct by redefining my variables, but I'm still struggling with
what functions will do the other aspects... but I have to think that someone
has done this before.
glm does...
2018 Apr 05
2
Obtain gradient at multiple values for exponetial decay model
Readers,
Data set:
t,c
0,100
40,78
80,59
120,38
160,25
200,21
240,16
280,12
320,10
360,9
400,7
graphdata<-read.csv('~/tmp/data.csv')
graphmodeld<-lm(log(graphdata[,2])~graphdata[,1])
graphmodelp<-exp(predict(graphmodeld))
plot(graphdata[,2]~graphdata[,1])
lines(graphdata[,1],graphmodelp)
Please what is the function and syntax to obtain gradient values for the model curve at
2018 Apr 05
0
Obtain gradient at multiple values for exponetial decay model
This smells like homework, which the Posting Guide indicates is off topic.
I am not aware of "the function" that will solve this, but if you know what a gradient is analytically then you should be able to put together a solution very similar to the code you already have with the addition of using the coef function.
--
Sent from my phone. Please excuse my brevity.
On April 5, 2018
2018 Apr 06
0
Obtain gradient at multiple values for exponetial decay model
Try
coef( graphmodeld )
And you don't need to approximate if you use the newdata argument to the predict function.
I think reading the "Introduction to R" that comes with R would help.
--
Sent from my phone. Please excuse my brevity.
On April 5, 2018 2:00:45 PM PDT, g l <gnulinux at gmx.com> wrote:
>> Sent: Thursday, April 05, 2018 at 4:40 PM
>> From:
2018 Apr 06
2
Obtain gradient at multiple values for exponential decay model
> Sent: Friday, April 06, 2018 at 4:53 AM
> From: "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us>
> To: "g l" <gnulinux at gmx.com>
> coef( graphmodeld )
>
coef(graphmodelp)
Error: $ operator is invalid for atomic vectors
A quick search engine query revealed primarily references to the dollar sign ($) operator which does not seem relevant to this