similar to: Determining Starting Values for Model Parameters in Nonlinear Regression

The cautions people have given about starting values are worth heeding. That nlxb() does well in many cases is useful, but not foolproof. And John Fox has shown that the problem can be tackled very simply too. Best, JN On 2023-08-19 18:42, Paul Bernal wrote: > Thank you so much Dr. Nash, I truly appreciate your kind and valuable contribution. > > Cheers, > Paul > > El El

Thank you so much Dr. Nash, I truly appreciate your kind and valuable contribution. Cheers, Paul El El s?b, 19 de ago. de 2023 a la(s) 3:35 p. m., J C Nash < profjcnash at gmail.com> escribi?: > Why bother. nlsr can find a solution from very crude start. > > Mixture <- c(17, 14, 5, 1, 11, 2, 16, 7, 19, 23, 20, 6, 13, 21, 3, 18, 15, > 26, 8, 22) > x1 <- c(69.98, 72.5,

Dear all, I have a big data matrix and I want to convert those data into weekly basis which means 7 days needs to be avaraged and aggregate a single value > dput(test) structure(list(locid = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,

I have a full data set like this: aa bas aas bms ams bcu acu omega y 1 ALA 0 127.71 0 69.99 0 -0.2498560 79.91470 outward 2 PRO 0 68.55 0 55.44 0 -0.0949008 76.60380 outward 3 ALA 0 52.72 0 47.82 0 -0.0396550 52.19970 outward 4 PHE 0 22.62 0 31.21 0 0.1270330 169.52500 inward 5 SER 0 71.32 0 52.84 0 -0.1312380 7.47528 outward 6

Hello, I have found a problem with using the glm function with a gamma family. I have a vector of data, assumed to be generated by a gamma distribution. The parameters of this gamma distribution are estimated in two ways (i) using the glm() function, (ii) "by hand", using the optim() function. I find that the -2*likelihood at the maximum found by (i) is substantially larger than that

The data set consists of two sets of matrices, as labelled by the columns, T's and C's. > xy x T1 T2 T3 T4 T5 C1 C2 C3 C4 C5 [1,] 50 0.00 0.00 33.75 0.00 0.00 0.00 36.76 0.00 35.26 0.00 [2,] 13 34.41 0.00 0.00 36.64 32.86 34.11 35.80 37.74 0.00 0.00 [3,] 14 35.85 0.00 33.88 36.68 34.88 34.58 0.00 32.75 37.45 0.00 [4,] 33 34.56

I am having trouble with optim. It claims to have converged to a minimum, yet it has in the course of the optimization visited many points which are closer to optimal. I would be grateful for any explanation of this behaviour. I'm trying to estimate the parameters in the model X ~ Binomial(1,p) * NegBin(mu,theta). So I define a log likelihood function, and invoke optim thus: o <- optim

Hi, Does anyone use Seagate ST32000542AS disks with ZFS? I wonder if the performance is not that ugly as with WD Green WD20EARS disks. Thanks, -- Piotr Jasiukajtis | estibi | SCA OS0072 http://estseg.blogspot.com

I am trying to obtain the Kruskal (1964) secondary least-squares monotonic transformation of a rank variable given 4 categorical variables in order to obtain optimal transformation for regression. The academic problem assigned is to compare R, SPSS (Conjoint Analysis), and SAS' proc transreg in speed and accuracy. Currently, SAS and SPSS are giving similar results, but R's are quite

Hi friends, I have a matrix with following format. group var1 var2 .......varN c1 group1 1.2399 1.4990....-1.4829 c2 group4 0.8989 0.7849.....1.8933 ... ... c100 group10 ..... I want to draw a profile plot of each condition c1 to c100, which rows in above matrix and each line representing a row should be uniquely colored according to the group(1 to 10). I think this is simple task

Dear R users, I have now tried out several options of obtaining p-values for (quasi)poisson lmer models, including Markov-chain Monte Carlo sampling and single-term deletions with subsequent chi-square tests (although I am aware that the latter may be problematic). However, I encountered several problems that can be classified as (1) the quasipoisson lmer model does not give p-values when

Thanks for everyone's input so far, it is greatly appreciated. But I've got one last task I could use some advice on Here are the first few lines of my data set: site,time_local,time_utc,reef_type_code,sensor_type,sensor_depth_m,temperature_c 06,2006-04-09 10:20:00,2006-04-09 20:20:00,BAK,sb39, 2, 29.63 06,2006-04-09 10:40:00,2006-04-09 20:40:00,BAK,sb39, 2, 29.56 06,2006-04-09

I'm able to recieve fax with pure SpanDSP 0.0.2 + Asterisk successfully but I have problems with some fax machine so I wanted to try using HylaFax to recieve Fax instead of SpanDSP hoping that it'll solve my problem. I'm trying to connect Asterisk with SpanDSP using iaxmodem. My system looks like this: ISDN <---> Asterisk <---> IAXModem <---> Hylafax Asterisk and

Hi, I tried to inverse a matrix but it doesn`t work. I hope somebody can help me. This is what I did. > kurse <- read.table("kurse.txt", header=T, dec=",") > x <- cbind(1,kurse[,-c(1)]) > y <- kurse$index > t(x) %*% x Error in t(x) %*% x : requires numeric matrix/vector arguments > x <- as.matrix(x) > xtxi <- solve(t(x) %*% x) Error in

Hello, Using the following lines of code, I created the following graph:

Hello, Using the following lines of code, I created the following graph:

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Hello, I would like to perform a Partial least square discriminate analysis (PLSDA) in R. To do this I use the package mixOmics. I could perform the PLSDA in R. however I would also like to perform a leave-one-out cross validation in order to assess the performance of my model. My supervisor told me that I should focus on the R2/Q2 ratios. However when I read the instruction for running the

https://bugs.freedesktop.org/show_bug.cgi?id=70389 Dennis Favro <dfavro at gmail.com> changed: What |Removed |Added ---------------------------------------------------------------------------- CC| |dfavro at gmail.com --- Comment #3 from Dennis Favro <dfavro at gmail.com> --- Getting what appears to be a

Dear list I try to run a bootstrap with lmer. I often, but not always, get the error message: Error in objective(.par, ...) : Leading minor of order 6 in downdated X'X is not positive definite (with the number (here 6) varying) In R-archives I came across some threads that treated this problem, nevertheless they refer to lmer when using it with family = "binomial", so the