similar to: extracting Std. Error value from lm/nls

Thanks for your reply Nassar. What I really want is to overlay (like add=TRUE) the plots 1 and 2. With plots "at the same screen" I meant overlaid and not one beside the other, i.e., only one plot with all the points (1 to 10) in blue (or any other color), the points 5 to 9 in red and a regression line from points 5 to 9. Best regards, Antonio Olinto ----- Original Message -----

Antonio, For linear regression we have the following identity total SS = regression SS + residual SS (*) where total SS is the sum of squares of observations around their mean, i.e. total SS = (n-1)*var(y) and residual SS is given by the deviance function. R-squared is defined as R^2 = regression SS/ total SS = 1 - residual SS/total SS. You can use this last formula

Hi, I'd like to find which values of x will give me a y. In other words, in the example of a gaussian curve, I want to find the values of x that will give me a density, let's say, of 0.02. curve(((1/(sqrt(2*pi)*10))*exp(-((x-50)^2)/(2*10^2))),xlim=c(0,100)) Thanks for any help, Antonio Olinto ------------------------------------------------- WebMail Bignet - O seu provedor do

Dear R-list members Here goes a question on data frames: I want to create a new data frame excluding some records (rows) from an existing one. Considering the data frame "fish.dat" at the end of this message, I can make a boxplot(Ring~Radius) and identify the points at rows 11 and 25 as outliers. With the command fish.dat[c(11, 25),] I can identify which fishes are related to

Dear R-list members, Some months ago I wrote a message on the usage of gnls (nlme library) and here I come again. Let me give an example: I have a 10 year length-at-age data set of 10 fishes (see growth.dat at the end of this message) and I want to fit a von Bertalanffy growth model, Li= Linf*(1-exp(-k*(ti-t0))) where Li = length at age i, Linf= asymptotic length, k= curvature parameter, ti=

Hello R-list members, I’m trying to make a min-avg-max plot (like a boxplot, without box and outliers, i.e., for each class of "x" a vertical line indicating the range (max-min) and an horizontal line or point indicating the mean) with data like: Year Avg Min Max 98 10 7 13 99 12 10 15 01 11 6 14 Which command should be used? Many thanks, Antonio Olinto

Hi, I want to write in x axis label "fitted value of lambda" (lambda in greek letter). xlab=expression(lambda) gives the "lambda", I tryed things like xlab=paste ("fitted value of ", expression(lambda)) but I didn't get the greek letter. Thanks in advance for any hint. Antonio Olinto ------------------------------------------------- WebMail Bignet - O seu

Hi, I have doubts in using subset command. I have a list of, lets say, 15 species and I want to make a subset with only 2 of them. I??m the command data2 <- subset(data1, species=="sp1"|species=="sp2") Nevertheless, when I ask for the summary (summary(data2)) the others species names still apearing. Also I tried data2<-data1(data1$species %in%

Hello, I'm trying to fit experimental data with a model and nls. For some experiments, I have data with x from 0 to 1.2 and the fit is quite good. But it can happen that I have data only the [0,0.8] range (see the example below) and, then, the fit is not correct. I would like to add a constraint, for example : the second derivative must be positive. But I don't know how to add this to

Hello, This is my first post to this list. Well, I tried to install Google Earth using WineTools but I got the "Unknown Graphics Card" error. I can open the program but Earth doesn't appear. I'm running Debian Sarge on a ASUS CUW(E)-FX motherboard (Intel 810 Chipset) and Gnome 2.10.2 inteface. Thanks for any help. Best regards, Antonio -- Ant?nio Olinto Biologist /

Hi, I have a dataframe with 3 columns: month (1 to 12), length and length class. I'm trying to make a cross table with the counts of lengths per length class and month. I don??t have all classes per month. | 1 2 3 ... ------------- 120 | 0 1 0 150 | 5 6 0 170 | 3 0 7 ... I have already tryed many commands, without success - unfortunately. May someone help me? Thanks in advance!

Dear R-List members, I want to check if a set of measurements follows better a gamma or a lognormal distribution (see data below). Using shapiro.test I can test for normality (shapiro.test(log (Lt)). To test for gamma (and normal) distribution I would use ks.test but I need to specify its shape and scale. How should I calculate these values in R? I tried > Lt.fit <- glm(Lt ~ 1,

Hi, I have a data set with values (L) varying from 1 to 700, with repeated numbers, and I want to sample them according to the probabilities given by a logistic curve P=1/(1+e(-r*(L-Lc))) where r gives "S" the inclination and Lc the "rotation point". P ranges from 0 to 1. As I could see I cannot use this P as prob in sample function. I'd need the probabilities as given by

Why fails nls with "singular gradient" here? I post a minimal example on the bottom and would be very happy if someone could help me. Kind regards, ########### # define some constants smallc <- 0.0001 t <- seq(0,1,0.001) t0 <- 0.5 tau1 <- 0.02 # generate yy(t) yy <- 1/2 * ( 1- tanh((t - t0)/smallc) * exp(-t / tau1) ) + rnorm(length(t))*0.01 # show the curve

Hi, Some time ago I asked about how to use comma as decimal separator in plots and Mr. Paul Murrell wrote: ------- You could try something with axis() and chartr(), like ... par(mfrow=c(2,1)) plot(1:10/11, rep(1, 10), main="Standard X-Axis") plot(1:10/11, rep(1, 10), main="Customised X-Axis", axes=F) axis(1, at=pretty(1:10/11),

I have data vectors x and y both with 179 observations. I'm trying to fit a nonlinear model with five parameters using nls. The formula is only defined within a range of x-values, it should be zero otherwise, thus my attempted use of ifelse: > df<-data.frame(x,y) >

Hello all, Here goes one of my first functions. I want to make a nonparametric multiple sample comparison with unequal sample sizes (see Zar?s Biostatistical Analysis, 3rd. Ed., pg. 201 Example 10.11, pg. 288 Example 11.10). In the real world, I want to compare samples of fish length captured with different fishing gears. After using the Kruskal-Wallis test I want to check the differences

Dear list members I have a doubt on how p-values for t-statistics are calculated in the summary of Linear Models. Here goes an example: x <- rnorm(100,50,10) y <- rnorm(100,0,5) fit1<-lm(y~x) summary(fit1) summary(fit1)$coef[2] # b summary(fit1)$coef[4] # Std. Error summary(fit1)$coef[6] # t-statistic summary(fit1)$coef[8] # Pr(>|t| summary(fit1)$df [2] # degrees of freedom #

This works fine: fit42<-nls(Vfs~SSlogis(Months,Asym.Int+Asym.Group*Groupdum,xmid,scal), data=df, start=c(Asym.Int=22,Asym.Group=5,xmid=2,scal=6), na.action=na.omit) But this, identical except using gnls, doesn't converge: fit43<-gnls(Vfs~SSlogis(Months,Asym.Int+Asym.Group*Groupdum,xmid,scal), data=df, start=c(Asym.Int=22,Asym.Group=5,xmid=2,scal=6), na.action=na.omit) Error in gnls(Vfs

I am trying to fit a nonlinear regression to infiltration data in order to determine saturated hydraulic conductivity and matric pressure. The original equation can be found in Bagarello et al. 2004 SSSAJ (green-ampt equation for falling head including gravity). I am also VERY new to R and to nonlinear regressions. I have searched the posts, but am still unable to determine why my data come up