similar to: Population Decay in R

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 gradient matrix at initial parameter estimates

I finally got (mostly) what I wanted. In an attempt to figure out how to get nls to deal with a non-differentiable function, I had (stupidly) 'simplified' the problem until it became singular. Can I do something to make optim() less sensitive to my initial guess? For this example, I get a lousy solution if I make the initial guess for t0 = min(t) = 0.05. Thanks again, -- Robert Merithew

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]]

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

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

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

Hi, I have created the plot below and have a few questions about changes. 1) How do I change the "Year" title of each plot so it reads from the top "2006","2007","2008","2009". 2) How do I get rid of those vertical grey bars in the title bar of each plot? I apologise for my ignorance... one of those days :( James

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

Hi, How do I tell an if statement to generate two seperate outputs. E.g If X>5 I want to create df1 and df2: if (X>5) {df1<-c(4,5,6,7,8) AND df2<-c(9,10,11,12,13)} Thanks, James -- View this message in context: http://www.nabble.com/If-statement-generates-two-outputs-tp22650844p22650844.html Sent from the R help mailing list archive at Nabble.com.

Dear R-Users I have 2 questions: Firstly, If I create a matplot and legend for multiple vectors and then tag another vector on using matlines (e.g. a 'total' of all vectors), is there anyway to add the new line to the legend without recreating it? I have created the plot this way because I would like to define the lty and lwd for the 'total' vector so that it can be

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

Hello, I'm sorry if this seems similar to my last post but I thought it was significantly different to warrent a new thread. Using the dataset below, is there a way to generate a bar/line plot for the TACC/Catch of every lvl of stock? i.e. OR1,OR3,OR5. The picture at the bottom of this post is an example of the bar/line plot for OR1 which was generated when OR1 was the only stock in the

Hi There, I have created the following function format<- function(){ repeat { form<-readline(paste("\nIn what format do you want to save these plots?\nChoose from: wmf, emf, png, jpg, jpeg, bmp, tif, tiff, ps, eps, or pdf.\nNote: eps is the suggested format for publication quality plots.\nPlot format --> ")); cat("\nI'm sorry, I don't know what that format

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). However I am getting

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

Hello all, When 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]

I thought I was finished, having gotten everything to work as intended. This is a model of risk, and the short term forecasts look very good, given the data collected after the estimates are produced (this model is intended to be executed daily, to give a continuing picture of our risk). But now there is a new requirement. I have weekly samples from a non-autonomous process (i.e. although well

Hi Guys, I was wondering how you would go about solving the following problem: I have a list where the grouping information is in the row names. Rowname [,1] X1Jan08 324 X1Jun08 65 X1Dec08 543 X2Jan08 23 X2Jun08 54 X2Dec08 8765 X3Jan08 213 X3Jun08 43 X3Dec08 65 How can I create the following dataframe: Value Date Group [1,] 324 Jan 08 X1 [2,] 65 Jun 08

Hi, I'm sure these are basic problems so I apologise in advance for my ignorance. I have a dataset with X, Y, and a Factor with 4 levels. I am trying to figure out how to use lm() to find the r2 value, slope and intercept of an X~Y regression, for each level of the Factor. Is there a way to do this automatically without having to specify different subsets of the factor? my code so far:

I am using library(nnet) to train up an ANN with what I believe is a moderately sized dataset, but R is complaining about too many weights: --- > nn.1 <- nnet(t(data), targets, size = 4, rang = 0.1, decay = 5e-4, maxit = 200) Error in nnet.default(t(data), targets, size = 4, rang = 0.1, decay = 5e-04, : Too many (1614) weights > dim(targets) [1] 146 2 > dim(data) ## Note