similar to: Question for LM intercept

Y X Z 42.0 7.0 33.0 33.0 4.0 41.0 75.0 16.0 7.0 28.0 3.0 49.0 91.0 21.0 5.0 55.0 8.0 31.0 data<-read.table("d.txt",header=TRUE) mod<-lm(data$Y~data$X+data$Z) --------------------------------------- I would like to know the predict value at a new level, say X=10 Z=30 Is there a function available to calculate it

Hi, I would like to enquire if by typing plot (lm(y~x)) would this show me the plot of the fitted line? I tried this function previously but I was only able to get the last 4 plots starting with Residuals vs fitted. Thank You. Melissa ************************************************************ JLT Risk Solutions Ltd 6 Crutched Friars, London EC3N 2PH. Co Reg No 1536540 Tel: (44) (0)20 7528

Dear All: I apologize for asking such an elementary question, but I could not find an adequate response on line. I am hoping to receive some help with the interpretation of the Intercept coefficient in the gam model below. I1 through I3 are dummy coded "Item difficulty" parameters in a data set that includes 4 items. If the Intercept is the value of Y when all other terms are 0, am I

Hey all, I'm using the gam() function inside the mgcv package to fit a penalised spline to some data. However, I don't quite understand what exactly the intercept it includes by default is / how to interpret it. Ideally I'd like to understand what the intercept is in terms of the B-Spline and/or truncated power series basis representation. Thanks!

Dear List, I ran a regression model using lm and produced a regression line using abline. The line ranges from -20 to 20 in x axis, and the section I only want is from -20 to 0. Please kindly advise any function in abline () to set the range of x axes. Thank you Elaine [[alternative HTML version deleted]]

Dear list, I want to retrieve the p-value of a two-polynomial regression. For a one-polynomial lm I can easily do this with: summary(lm(b~a, data=c)[[4]][[8]]. But how do I find the final p-value in the two-polynomial regression? Under $coefficients I don't find it Any suggestions? Patrick alt <-(2260,2183,2189,1930,2435, 2000,2100,2050,2020,2470, 1700,2310,2090,1560,2060,

Hi R, This is a problem, which I have tried to present in a simple way: Let, x1=1:10 x2=2:11 y=2+3*x1 lm_obj=lm(y~x1+x2) lm_obj step(lm_obj) # Step function for the first time y=y^0.1 lm_obj step(lm_obj) #Step function after a transformation on Y, but 'lm_obj' is not modified. The two step function behave differently. The first one is before the

Dear List, Apologies for this off-topic post but it is R-related in the sense that I am trying to understand what R is telling me with the data to hand. ROC curves have recently been used to determine a dissimilarity threshold for identifying whether two samples are from the same "type" or not. Given the bashing that ROC curves get whenever anyone asks about them on this list (and

I am using the clever formula notation of R to first do an OLS. E.g. I say m <- lm(y ~ x + f) where f is a factor, and R automatically constructs the dummy variables. Very nice. I need to then go on to do some other ML estimation using the same design matrix that's used for the OLS. I could, of course, do this manually. But it seems that lm() has done all this hard work. I wonder if

Dear List, A student in the Department where I work would like to produce a graphic similar to this one: http://image.guardian.co.uk/sys-files/Guardian/documents/2009/09/16/Public_spending_160909.pdf Does anyone know if the figure in the pdf can be generated in a specific software application for example? Any suggestions would be most gratefully received by the student concerned. Many thanks,

Dear all, I don't know what's my question is called. I have a performance variable A, such as sales. And I have another variable B, let's say establish time of firm. I want to create the third variable that is sales without the effect of establish time. Maybe it can be called partial effect problem. I'm not sure. Does anyone have any suggestion? Thank you in advance! All the

Dear all, How can I run a constrained correspondence analysis with the following data: 15 animals were measured repeatedly month-wise (over to 2 years) according to ther diet composition (8 food categories). our data.frame looks like this: food 1 2 ... 8 sex season year animal freq 12 8 ... 1 0 summer 2011 1 freq 0 7 ... 0 1 winter 2011 1 ... freq 0 7 ... 0 1 spring 2011 15 We

I think this is one for Gabor. I don't seem to be able to find my way to an answer despite numerous rereadings of factor and table. Here is a toy example: ### Some data EthnicCode <- c("European/Other", NA, "European/Other", "European/Other", "Pacific", "European/Other", "European/Other",

Hi, I have faced a problem with the merge() function when trying to merge two data frames that have a common index but the second one does not have cases for all indexes in the first one. With usual variables R fills in the missing cases with NA if all=T is requested. But if the variable is a matrix R seems to insert NA only to the first column of the matrix and fill in the rest of the columns by

https://bugzilla.mindrot.org/show_bug.cgi?id=1824 Summary: Added project(4) support for Solaris 10 Product: Portable OpenSSH Version: -current Platform: All OS/Version: Solaris Status: NEW Severity: normal Priority: P2 Component: sshd AssignedTo: unassigned-bugs at mindrot.org ReportedBy:

Hello there, I'm trying to plot vectors with p<0.1 in a NMDS ordination plot using p.max. Below the scripts I'm using. I guess I'm missing something! could you please give me a hand? species<-metaMDS(species_matrix)ef<-envfit(species,environmentaldata_file,permu=999,na.rm=TRUE)efplot(species, dis="sites")plot(ef,p.max=0.1) Error in plot.envfit(ef, p.max = 0.1) :

Dear List, I need to add a subscript and a superscript to some of the ions in the labels on some plots. I have got to here but now I'm stuck: plot(1:10, xlab = expression(paste("nm SO"[4], " ", mu, "eq cm"^{-2}, " yr"^{-1}))) Which gives almost what I require. No matter what I tried, however, I could not get bot a sub script *and* a superscript

Dear List, Some independent variable were missing in calculation using lm and glm (gaussian). (X= Y1+Y2+…..+Y16, Independent number: 16 variable) However, those variables did work well in cor(X, Y) respectively. str(dataframe) was also run to ensure that the variables were all numbers. Moreover, the missing variables were different in lm and glm. In lm, 3 factors were not taken into

No the solution is to use sssd ??? ________________________________ De: Themis Hoffmeister Villegas <themis.villegas at outlook.com> Enviado: quinta-feira, 7 de novembro de 2019 16:25 Para: samba at lists.samba.org <samba at lists.samba.org> Assunto: NT_STATUS_ACCESS_DENIED (0xc0000022, authoritative=0) Good afternoon friends I have a problem with SAMPA My environment has several

Hi all, thank you for your answers; i've tried both cca from vegan library, and dudi.coa from ade4 library; one last question: my deal is mainly with contingency tables, like the one i'm posting here acciaieria<-c(.41,.02,.44,.04,.09) laminatoio<-c(.34,.28,.26,.01,.11) fonderia<-c(.48,.05,.34,.08,.05) leghe<-c(.45,.19,.25,.03,.08)