similar to: A basic design question for R

Hi All I have a dataframe: myframe<-data.frame(ID=c("first","second"),x=c(1,2),y=c(3,4)) And I have a function myfun: myfun<-function(x,y) x+y I would like to write a function myfun2 that takes myframe and myfun as parameters and returns a list as below: mylist $first [1] 4 $second [2] 6 Could you please help me with this? Doesn't seem like the

R-Help community, I understand that data.frames can hold elements of type double, string etc but NOT objects (such as a matrix etc). This is not convenient for me in the following situation. I have a function that takes 2 inputs and returns a vector: testfun <- function (x,y) seq(x,y,1) I have a data.frame defined as follows: testframe<-data.frame(xvalues=c(2,3),yvalues=c(4,5)) I would

Apologees the novice question. Currently climbing up the learning curve of R. Suppose I have the following function and the data.frame: testfun<-function(x=1,y=2) x+y testframe=data.frame(col1=c(1,2),col2=c(3,4)) When evaluating testfun, I want to use the default value for y (which is 2) and for x, I want to feed (one by one) the values in col2 of testframe. How can I achieve this please?

Dear R community, My question is not a quick fix one but it would be helpful if you have any advice for me. I have a large data set of many locations in the US and all of these locations are expressed in coordinates (longitudes and latitudes). I need a tool which returns the state that each location is situated in. So the program should return me a vector of state names (eg. NY,CA,OH, etc).

Hola. Como te dijo Carlos, el problema está en los nombres de las columnas y en los nombres de las filas. Cuando hice la importación (con dd<-read.csv('mortality.csv'), tuve problemas con las filas de nombre: - Malignant tumour of the larynx trachea bronchus and lungs - Malignant tumour of the lip pharynx and mouth - Other endocrinological metabolic and nutritional conditions

Estimados Queremos con el paquete FactoMineR hacer este tipo de tabla de mortalidad que lea los datos desde de una tabla csv Realizamos lo que viene en la ayuda y es muy interesante, sin embargo cuando mandamos a leer desde la tabla csv original de los autores no hace el análisis porque algo falta y no nos percatamos de que es. Adjunto tabla original Saludos cordiales #ESTO ES LO QUE

Dear R Users: I have the individual mortality rate and 95% CI of 100 hospitals, how to do the plot with the individual hospital in the Yaxis, and the mortality rate and 95% CI in the Xais and a overall mean as a reference line? Thanks and regards, Xin [[alternative HTML version deleted]]

Dear listeRs; I am hoping to provide myself the ability to interpolate mortality estimates within intervals for a range of conditions and ages. I have four mortality tables derived from the Society of Actuaries 2001 VBT tables that contains interval mortality rates by starting age and year of duration. I would like to flexibly interpolate using a large set (~4MM) of ages and conditions

Hello, I am using Dotplot (from Frank Harrell's HMISC library) to make a graph of rates with confidence intervals but I get a 'black' background -- nice but not on a printed document: >Dotplot(group~Cbind(rate,lower,upper)|mortality,data=mort,ylab=' ') How do I change the background (and other) collors in Dotplot? Thanks for you help. Marwan Khawaja platform

I am wondering if there is an R function that could estimate a generalized nonlinear mixed model. >From my reading it seems that nlme from the nlme package can fit nonlinear mixed models, while lmer from the lme4 package can fit generalized linear mixed models. One alternative I?ve found is gnlmix from the repeated package, although this only allows for a single random effect. Is there

I am doing a reanalysis of results that have previously been published. My hope was to demonstrate the value of adoption of more modern regression methods in preference to the traditional approach of univariate stratification. I have encountered a puzzle regarding differences between I thought would be two equivalent analyses. Using a single factor, I compare poisson models with and without

Hi all, Here is my problem: I performed bioassays using a unique insecticide on 9 different genotypes and got their mortality depending on the dose of insecticide used. Now, I want to see wether some genotypes are different or not in their responses to insecticide. My problem is that I have up to four replicates for some genotypes, but only one for other... Due to this unbalanced design, I

i am trying to replicate the following graph using xyplot : attach(x) plot ( jitter(type), mortality, pch=16, xlim = c(0.25, 3.75)) lines ( c(1-0.375,1.375) , c ( median(mortality[type==1]), median(mortality[type==1])), lwd=5,col=2) lines ( c(2-0.375,2.375) , c ( median(mortality[type==2]), median(mortality[type==2])), lwd=5,col=2) lines ( c(3-0.375,3.375) , c ( median(mortality[type==3]),

Hola, El problema está con el nombre de las columnas y las filas del fichero que importas. Mira este detalle tras hacer la importación: > names(mort) [1] "X" "X15.24..79." "X25.34..79." [4] "X35.44..79." "X45.54..79." "X55.64..79." [7] "X65.74..79." "X75.84..79."

Hi, I am using the package "demography" from Rob Hyndman for the Lee-Carter-Model. It is an amazing powerful tool but I am struggling with one issue: I want to compute different percentiles of the survival probability distribution derived from the Lee-Carter-Forecast (e.g. the 50%tile, 60%tile, 75%tile and 99%tile) for each of the next 10 years. Is there any possibility to retrieve

Hello, all. I have co-opted a number of functions that can be used to plot the hazard/survival functions and associated density distribution for a Gompertz mortality model, given known parameters. The Gompertz hazard model has been shown to fit relatively well to the human adult lifespan. For example, if I wanted to plot the hazard (i.e., mortality) functions: pop1 <- function (t) {

Hi all, I am not sure how to handle interactions with categorical predictors in the GAM models. For example what is the different between these bellow two models. Tests are indicating that they are different but their predictions are essentially the same. Thanks a bunch, > gam.1 <- gam(mortality.under.2~ maternal_age_c+ I(maternal_age_c^2)+ + s(birth_year,by=wealth) + +

Dear all, I'm trying reproduce an example of bioassays Yielding Concentration-Mortality Data particularly control - adjustment model from book Bioassay of Entomopathogenic Microbes and Nematodes chapter 7 with R. I used glm with family=binomial and link=probit, but I do not know how to implement parameter gamma (control mortality - mortality of the untreated control insect in this exaple)

Hallo Everybody How do you specify arguments for a function used within another function? Here is my problem: I am reconstructing a calculator for the burden of disease due to air pollution from publications and tools published by the WHO. The calculations make use of published dose-response relationships for particular health end-points. This is then applied to populations with known or

Hi I am trying to carry out some maximum likelihood estimation and I'm not making much headway, and I'm hoping that someone will be able to point me in the right direction. I am modelling mortality statistics. One way to do this is to model the mortality rate (or, more accurately, log of the mortality rate, log_m) as (say) a constant plus a proportion of age, plus time, so: r_1 <-