similar to: Newly installed version; can't run lm function

Dear R-devel list, I realized that removing a predictor in lm through the "-"'s operator in formula() does not affect the complete cases that are considered. A minimal example is: summary(lm(Wind ~ ., data = airquality)) # 42 observations deleted due to missingness summary(lm(Wind ~ . - Ozone, data = airquality)) # still 42 observations deleted due to missingness, even if only 7

> On Jun 21, 2017, at 9:11 AM, Evan Cooch <evan.cooch at gmail.com> wrote: > > Suppose I have the following sort of dataframe, where each column name has a common structure: prefix, followed by a number (for this example, col1, col2, col3 and col4): > > d = data.frame( col1=runif(10), col2=runif(10), col3=runif(10),col4=runif(10)) > > What I haven't been able to

Dear All Hopefully someone out there can point out what I am missing! I have a (large, several hundred) dataset of gardens in which over two years the presence/absence of a particular bird species is noted each week. I have good reason to believe there is a difference between the two years in the weekly proportion of gardens and would like to assess this, before going on to look in more detail at

> library(reshape2) > x = melt(airquality, id=c('month', 'day')) With reshape I can cast with multiple functions: > library(reshape) > cast(x, month+variable~., c(mean,sd)) month variable mean sd 1 5 ozone 23.615385 22.224449 2 5 solar.r 181.296296 115.075499 3 5 wind 11.622581 3.531450 4 5 temp 65.548387

R-help, I'm using the "update" command for a multiple regression model and it is just not working: > update(model1, . ~ . – temp:wind:rad,data=ozone.pollution) Error: unexpected input in "model2<-update(model1, . ~ . –" > summary(model1) Call: lm(formula = ozone ~ temp * wind * rad + I(rad^2) + I(temp^2) + I(wind^2), data = ozone.pollution) Residuals:

I'm not sure if this is a bug, or if I'm doing something wrong. =20 =46rom the worms dataframe, which is at in a file called worms.txt at =20 http://www.imperial.ac.uk/bio/research/crawley/therbook <http://www.imperial.ac.uk/bio/research/mjcraw/therbook/index.htm>=20 =20 the idea is to extract a subset of the rows, sorted in declining order of worm density, with only the maximum

I want to estimate the effect of several independent variables on several dependent variables. In the example below I wanted to estimate the effect of three independent variables on ozone and temperature. My aim is to create a list of dependent and independent variables and automate the process rather than writing every dependent and independent variable in each model as I have done below.

Hi Gustav, Try this: lapply(1:length(models),function(i) lapply(models[[i]],function(x) summary(x)$coef[2,]))[[1]] #1st list component [[1]] #??? Estimate?? Std. Error????? z value???? Pr(>|z|) # pm10 #5.999185e-04 1.486195e-04 4.036606e+00 5.423004e-05 #[[2]] #??? Estimate?? Std. Error????? z value???? Pr(>|z|) #ozone #0.0010117294 0.0003792739 2.6675428048 0.0076408155 #[[3]] #???

I think I've gotten my Emacs/Sweave/R system set up correctly, thanks to Vincent and Jim, but I haven't been successful getting my first document produced. I'm trying to use one of Friedrich Leisch's examples, http://www.ci.tuwien.ac.at/~leisch/Sweave/example-1.Snw. I cut and pasted the text into a document sweaveexample.Rnw in Emacs. It seemed to be processed successfully with R:

Hello Given the following data for a data set called airquality. To identify the nature of the objects from the data set airquality example "Ozone" would it be best to use the command is. like is.character(airquality$Ozone) ....... I tried attributes(airquality$Ozone) but it came up null. Would there be a better way to identify these objects. Thanking you in advance for your

Dear all, I have a problem with interactions in lmer. I have 2 factors (garden and gebiet) which interact, plus one other variable (home), dataframe arr. When I put: / lmer (biomass ~ home + garden:gebiet + ( 1|Block), data = arr)/ it writes: /Error in lme4::lFormula(formula = biomass ~ home + garden:gebiet + (1 | : rank of X = 28 < ncol(X) = 30/ In the lmer help I found out that if not

Hi! I have some questions about MARS model's coefficient of determination. I use the MARS method in my master's thesis and I have noticed some problems with the MARS model's R^2. You can see the following example that the MARS model's R^2 is too big when i have used mars() -function for MARS model building, and when I have made MARS-model using a linear regression, it

>>>>> peter dalgaard <pdalgd at gmail.com> >>>>> on Mon, 26 Jun 2017 13:43:28 +0200 writes: > This seems to be due to changes made by Martin Maechler in > 2008. Presumably this fixed something, but it escapes my > memory. Yes: The change set (svn -c46441) also contains the following NEWS entry BUG FIXES o

hi all, I often have a data frame like this example data.frame(sq=c(1,1,1,2,2,3,3,3,3),area=c(1,2,3,1,2,3,1,2,3),habitat=c("garden","garden","pond","field","garden","river","garden","field","field")) for each "sq" I have multiple "habitat"s each with an associated "area". I

I hope my problem is not too basic to post here. I am a beginner having problems with some matrix manipulation. The data I am working with are sites with hourly ozone readings and is in a matrix where each row is a site and each column is an hourly reading. So for 10 sites, one day's worth of data is a 10x24 matrix - column 1 is the ozone measurement for midnight GMT, column 2 is ozone at

Gracias a los tres, Raúl, Marcelino y Carlos. Lo del "get" de Marcelino me da la respuesta a lo que yo exactamente preguntaba, y funciona, pero ahora tengo problemas con el for, por lo que probablemente recurra al eval parse de Raúl o Carlos, que ya tienen el for. Aún así, lo intento 1º con el get. Con subset(df, subset=get(GT[i])>0) el problema es que en el for hago un

Hi just a quick inquiry Sorry if this is too trivial but I am just a beginner in R. I am looking at the plyr package and I am intrigued at how data(i.e. ozone, baseball) is loaded without having to type data(ozone). Are they automatically loaded when i call library(plyr)? I want to do the same thing when I make my package. How does one accomplish this? Also, are there any beginner guides on how

Gracias Marcelino. Si, (i in 1:length(GT)), lo he utilizado mil veces, pero se me sigue olvidando de una vez a otra. Lo iba a mirar, pero me centré primero en que me hiciera bien el mapa. He probado el for y me da este error: Error in aes(x = lon, y = lat, color = get(GT[i]), size = 2) + scale_colour_gradient(low = ("white"), : non-numeric argument to binary operator

I want to 1) Select for each of the n points in a matrix A, those of the m points in B that lay within a given radius. 2) Of those points within the radius, select the k nearest ones. What I now do is 1) Create an n*m matrix C were I put the distances from all the points in B to the points in A and make NA those cells were the distance is larger than the radius. (The points are geographical

Hi all, We are facing a problem while introducing ourselves to Reshape package use. Melt seems to work fine, but cast fails when we use mean as fun.aggregate. As you see here, length and sum work fine, but mean throws this same error whatever dataset we use. > cast(aqm, month ~ variable, length) month ozone solar.r wind temp 1 5 26 27 31 31 2 6 9 30 30