search for: dnase

Hello, my data is sorted by start.ens (see below). And now I would like to extract all rows (so called* defined row*s) with type==Expression - subset (df, type==Expression) - and the aforegoing type==DNase HS (which is not necessarly row n-1 - assumung that the defined row is n). I dont know how to add this to my subset command. Is that possible? Thanks Hermann > df start.ens fc.trans type end.ens peak end.grcm38 dpeak 1 9191942 0.9379 Expresssion NA NA NA NA 2...

Hi folks, Win7 64bit I tried to save DNase, a data set on database, as .txt file for future use with load. I can't do it on fly; > save(DNase, file="C:/Users/satimis/Documents/aaa.txt") > load(file="C:/Users/satimis/Documents/aaa.txt") > aaa Error: object 'aaa' not found > aaa.txt Error: object...

I'm wondering whether AIC scores extracted from nls() objects using AIC() are based on the correct number of estimated parameters. Using the example under nls() documentation: > data( DNase ) > DNase1 <- DNase[ DNase$Run == 1, ] > ## using a selfStart model > fm1DNase1 <- nls( density ~ SSlogis( log(conc), Asym, xmid, scal ), DNase1 ) Using AIC() function: > AIC(fm1DNase1) [1] -78.41642 Using number of estimable coefficients (including residual error): > -2*lo...

...(0,1,col=2) > ##D } > ##D mtext(expression("P-P plots : Noncentral "* > ##D chi^2 *"(n=1000, df=X, ncp= 1.2)"), > ##D cex = 1.5, font = 2, outer=TRUE) > ##D par(op) > ## End(Not run) > > > > cleanEx(); ..nameEx <- "DNase" > > ### * DNase > > flush(stderr()); flush(stdout()) > > ### Name: DNase > ### Title: Elisa assay of DNase > ### Aliases: DNase > ### Keywords: datasets > > ### ** Examples > > data(DNase) > coplot(density ~ conc | Run, data = DNase, + show =...

...ability to fix one (or more) of the coefficients that would normally be optimised (e.g. fix b3=0.8). Examples; based on and using data from example(SSgompertz) #--------------------- # vanilla call to nls, no coefficients fixed, works fine nls(density ~ SSgompertz(log(conc), Asym, b2, b3), data = DNase.1) #------------------------------------- # naive attempt to fix one parameter. I don't believe the error message nls(density ~ SSgompertz(log(conc), Asym, b2, b3=0.8), data = DNase.1) # Error in nlsModel(formula, mf, start, wts) : # singular gradient matrix at initial parameter estimates #-...

...and random effects without a startup object ? I thought it would be a mixture of nls and lme. after trying very hard, I ask for help on using nlme. Can someone hint me to some examples? I constructed a try using the example from nls: #variables are density, conc and Run #all works fine with nls DNase1 <- subset(DNase, Run == 1 ) fm2DNase1 <- nls( density ~ 1/(1 + exp((xmid - log(conc))/scal)), data = DNase1, start = list(xmid = 0, scal = 1), trace = TRUE) #Now I want to do a mixed model with covariate Run #how is the syntax? DNase1...

What am I failing to understand here? The script below works fine if the dataset being used is DNase1 <- DNase[ DNase$Run == 1, ] per the example given in help(nlrob). Obviously, I am trying to understand how to use nls and nlrob to fit curves to data using R. #package=DAAG attach(codling) plot(pobs~dose) #next command returns 'step factor reduced below min factor error' m.n...

...07-16 at 03:50, Peter.Caley at csiro.au wrote: > > I'm wondering whether AIC scores extracted from nls() objects using > > AIC() are based on the correct number of estimated parameters. > > > > Using the example under nls() documentation: > > > > > data( DNase ) > > > DNase1 <- DNase[ DNase$Run == 1, ] > > > ## using a selfStart model > > > fm1DNase1 <- nls( density ~ SSlogis( log(conc), Asym, > xmid, scal ), > > DNase1 ) > > > > Using AIC() function: > > > > > AIC(fm1DNase1) > &g...

Hola amigos, Supongamos que se quiere ejecutar un modelo no lineal con nls. Pensemos en el ejemplo de la ayuda: DNase1 <- subset(DNase, Run == 1) fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1) summary(fm1DNase1) Aquí se está modelando la densidad óptica de un ensayo relacionada de forma no lineal (logística) con (el logaritmo) de la concentración de una proteína. ¿Sabe alguien si...

Hello, I have start and end coordinates from different experiments (DNase hypersensitivity data) and now I would like to combine overlapping intervals. For instance (see my test data below) (2) 30-52 and (3) 49-101 are combined to 30-101. But 49-101 and 70-103 would not be combined because they are on different chromosomes (chr a and chr b). Does anybody have an idea? Th...

...weights into account while nobs.nls() does not. Admittedly, the help page of nobs() states that: For 'lm' and 'glm' fits, observations with zero weight are not included. i.e. does not comment on what nls does. But I wonder whether the following behaviour is desirable: R> DNase1 <- subset(DNase, Run == 1) R> fm3DNase2 <- nls(density ~ Asym/(1 + exp((xmid - log(conc))/scal)), + data = DNase1, weights=c(0,rep(1,14),0), + start = list(Asym = 3, xmid = 0, scal = 1)) R> nobs(fm3DNase2) [1] 16 > logLik(fm3DNase2) 'log Lik.' 42.62777 (df=...

...Sales Data with Leading Indicator BJsales.lead (BJsales) Sales Data with Leading Indicator BOD Biochemical Oxygen Demand CO2 Carbon Dioxide uptake in grass plants ChickWeight Weight versus age of chicks on different diets DNase Elisa assay of DNase EuStockMarkets Daily Closing Prices of Major European Stock Indices, 1991-1998 Formaldehyde Determination of Formaldehyde HairEyeColor Hair and Eye Color of Statistics Students Harman23.cor Harm...

Full_Name: Tadashi Kadowaki Version: 2.4.0 OS: Redhat Linux 9 Submission from: (NULL) (58.12.166.67) Doesn't nls function support subset? It seems not to work. And, there are no information in the online help. Has it sunk into oblivion?

Dear list, I have encountered a problem with predict.nls (Windows XP, R.2.5.0), but I am not sure if it is a bug... On the nls man page, an example is: DNase1 <- subset(DNase, Run == 1) fm2DNase1 <- nls(density ~ 1/(1 + exp((xmid - log(conc))/scal)), data = DNase1, start = list(xmid = 0, scal = 1)) alg = "plinear", trace = TRUE) Now consider prediction: > predict(fm2DNase1) [1] 0....

...y of a model for a large number of experimental data I thought it to be interesting to check the information provided by the summary method programmatically. Still I could not find out which method to use to get to those data. Example (not my real world data, but to show the point): [BEGIN] > DNase1 <- subset(DNase, Run == 1) > fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1) > summary(fm1DNase1) Formula: density ~ SSlogis(log(conc), Asym, xmid, scal) Parameters: Estimate Std. Error t value Pr(>|t|) Asym 2.34518 0.07815 30.01 2.17e-13 **...

I?m new to R so maybe this issue has been asked before and I still could not read the complete set of past messages sent to the list. I found a weird behabiour that I will explain with a simple example. Lets consider the following block of commands: > x <- diag(c(1,4,10)) > x [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 4 0 [3,] 0 0 10 > invx <- x^-1 > invx

Dear all, I encounter some discrepancies when comparing the deviance of a weighted and unweigthed model with the AIC values. A general example (from 'nls'): DNase1 <- subset(DNase, Run == 1) fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1) This is the unweighted fit, in the code of 'nls' one can see that 'nls' generates a vector wts <- rep(1, n). Now for a weighted fit: fm2DNase1 <- nls(density...

Dear All, I encounter some discrepancies when comparing the deviance of a weighted and unweigthed model with the AIC values. A general example (from 'nls'): DNase1 <- subset(DNase, Run == 1) fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1) Now for a weighted fit: fm2DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1, weights = rep(1:8, each = 2)) in which I assign increasing weights for...

Hi, I am trying to run the following nonlinear regression model. > nreg <- nls(y ~ exp(-b*x), data = mydf, start = list(b = 0), alg = "default", trace = TRUE) OUTPUT: 24619327 : 0 24593178 : 0.0001166910 24555219 : 0.0005019005 24521810 : 0.001341571 24500774 : 0.002705402 24490713 : 0.004401078 24486658 : 0.00607728 24485115 : 0.007484372

...ar sirs It seems like there is a bug in `profile.nls` with `algorithm = "plinear"` when a matrix is supplied on the right hand side. Here is the bug and a potential fix ##### # example where profile.nls does not work with `plinear` but does with # `default` require(graphics) set.seed(1) DNase1 <- subset(DNase, Run == 1) x <- rnorm(nrow(DNase1)) f1 <- nls(density ~ b1/(1 + exp((xmid - log(conc))/scal)) + b2 / x, data = DNase1, start = list(xmid = 0, scal = 1, b1 = 1, b2 = 1)) coef (f1) #R> xmid scal b1 b2 #R> 1.5055308 1.0455951 2.37079...