search for: continous

Hello, I have read through the manuals and can't seem to find an answer. I have a categorical, character variable that has hundreds of values. I want to group the existing values of this variable into a new, derived (categorical) variable by applying conditions to the values in the data. For example, suppose I have a data frame with variables: date, country, x, y, and z. x,y,z are

...h smooth OR linear term (but not both) for each variable: dd <- dredge(gam1, subset=(!`s(x1)` | !x1) & (!`s(x2)` | !x2) & (!`s(x3)` | !x3)) But I'm not sure at all how to apply these instructions to my data My formula is GAM<-gam(Species richness (count) ~ Categorical + Continous + Continous + * s*(Continous ) + Continous : Continous + Continous : Continous, family=quasipoisson, data =) Thanks for any advice on script Karen [[alternative HTML version deleted]]

How to define bounds for a semi continous variable in lp_solve. Min 5x1 +9x2 +7.15x3 +0.1x4 subject to x1+x2+x3+x4=6.7 x1+x4 <= 6.5 And x3 can be 0 or greater than 3.6 hence x3 is a semi continous variable how to define bounds as well as semicontinous function because using set.semicont and set. bound simantaneously doesn't seem...

Hi.. There are my nested routes map.resources :continent do |continent| continent.resources :land do |land| land.resources :destination end end By example it generates this url http://example/continent/azie/land/japan/destination/aomori I want http://example/continent/azie/japan/aomori How can i realize this...? Grtz...remco -- Posted via

Hi, I ran the following model using nlme: model2<-lme(log(malrat1)~I(year-1982),random=~1|Continent/Country,data=wbmal10) I'm trying to run a Poisson GlMM to avoid the above transformation but I don't know how to specify the model using lmer in the lme4 library: model3<-lmer((malrat1)~I(year-1982) + ??,data=wbmal10,family=poisson) How can I introduce a random factor of the

Hello, my dataset is already aggregated: I have two categorical variables, say "continent" and "country" and one non-negative metric variable "population". Now I would like to produce a mosaic plot which uses "population" to determine how large each area of the plot is. In other words, I fail to find out - how to use the mosaic function of the vcd package

Please explain me as what it means and how this analysis can be done using R and which library(ies) are needed. Thanks -- View this message in context: http://www.nabble.com/Regression-using-age-and-Duration-of-disease-as-a-continous-factors-tp24574133p24574133.html Sent from the R help mailing list archive at Nabble.com.

...for creating my Webtv for creating a continuos streaming of some files In the filename filed of Ezstream xml configuration i put a simple m3u playlist. My problems begin when ezstream begin to encode and stream the second file: If a use a system player , like Vlc or totem , the stream it's continous , if I use a web player like Cortado or Itheora , they stop to play when ezstream change from two file (for exampl from the first to second) How I can solve my problem? If you see visonair.tv ( see http://82.165.31.84:443 ), they use icecast how streaming server , and cortado . On their site th...

...for creating my Webtv for creating a continuos streaming of some files In the filename filed of Ezstream xml configuration i put a simple m3u playlist. My problems begin when ezstream begin to encode and stream the second file: If a use a system player , like Vlc or totem , the stream it's continous , if I use a web player like Cortado or Itheora , they stop to play when ezstream change from two file (for exampl from the first to second) How I can solve my problem? If you see visonair.tv ( see http://82.165.31.84:443 ), they use icecast how streaming server , and cortado . On their site th...

I have two tables CREATE TABLE continents ( id int(11) NOT NULL auto_increment, name varchar(255) NOT NULL, PRIMARY KEY (id) ) ENGINE=InnoDB DEFAULT CHARSET=utf8; CREATE TABLE countries ( id int(11) NOT NULL auto_increment, name varchar(255) NOT NULL, continent_id int(11) NOT NULL, PRIMARY KEY (id) ) ENGINE=InnoDB DEFAULT CHARSET=utf8; I generate scaffolds for country and for

...ariables are dichotomous factors, continuous (numerical) and ordered factors. I would like to calculate the linear correlation between every pair of my variables, because I would like to perform a logistic regression (glm()) without the correlation between variables. I thought I could use for the continous (numerical) and ordered factor a spearman correlation that is using the ranks. But I thought also that I have to use a contingency table for the dichotomous factors. I read also that it is possible to use a point-biserial correlation to calculate the correlation between dichotomous and continuou...

I have a data set which contains two columns. The first column is a list of countries, and the second column contains their political risk ratings. I would like to create one large plot that contains 5 different sections, each with a scatter plot. To clarify, I have divided the countries into 5 groups. For each group (continent), I would like to have the name of the continent on the x-axis, and

Hello How can I select several not continuous rows ? If I wanted to select rows 1 to 7 I'll write mydata[,1:7] But what if I need to select rows 1 to 5 and 10 to 15? -- View this message in context: http://r.789695.n4.nabble.com/How-to-select-not-continous-rows-tp3003840p3003840.html Sent from the R help mailing list archive at Nabble.com.

Dear all. Is it possible to convert.identify iso3 country names to the seven continent names? # Asia, Africa, Antarctica, Australia, Europe, South America, and North America, I have tried the following: ### region <- merge(countryExData,df,by.x='ISO3V10',by.y='iso3') where df is the name of my dataset with iso3 the identification variable but there seems to be a a lot of

...for an R solution I thought this was the best place: I would like to calculate the entropy for a variable and the conditional entropy between two variables, H(X|Y) for variables X & Y I have coded the case for the categorical case but I'm having problems understanding how to do it for the continous case. >From what I understand, for continous variables the entropy would be \integral_{A} f(x) log( f(x) ) dx where f(x) is the density of X and A is the support. I have tried obtaining the density of X by using the density estimation methods of the KernSmooth package and then doing a numeri...

Dear All, This may be a silly question, but I have tried searching through a few of the existing threads already, and haven't found any information on this. I am trying to color code entire continents/regions (Asia, North America, Africa, etc.) based on the number of relevant companies. The data would look like: World Location Companies North America 4848 Western Europe 1972 East Asia

> On Sep 7, 2017, at 11:36 AM, Miluji Sb <milujisb at gmail.com> wrote: > > Dear all. > > Is it possible to convert.identify iso3 country names to the seven > continent names? > > # Asia, Africa, Antarctica, Australia, Europe, South America, and North > America, > > I have tried the following: > > ### > region <-

Hi All.. Am working on continous backup of mailboxes using rsync(for e.g by running rsync every 2 min) Things gets more complicated when users create Subfolders in INBOX , SENT , etc.. If anyone among you did that plz guide & advise. Thanks CoolAtt ______________________________________________________________...

Dear R Users, R Core Team, I have a two dimensional space where I measure a numerical value in two situations at different points. I have measured the change and I would like to test if there are areas in this 2D-space where there is a different amount of change (no change, increase, decrease). I don´t know if it´s better to analyse the data just with the coordinates or if its better to group them

...t; > > > > dd <- dredge(gam1, subset=(!`s(x1)` | !x1) & (!`s(x2)` | !x2) & (!`s(x3)` | > !x3)) > > > But I'm not sure at all how to apply these instructions to my data > > > My formula is > > GAM<-gam(Species richness (count) ~ Categorical + Continous + Continous + > *s*(Continous ) + Continous : Continous + Continous : Continous, > family=quasipoisson, data =) > > > Thanks for any advice on script > > > Karen > > > > > -- Karen Moore PhD Researcher, FORESTBIO, Department of Botany, Trinity College Dubli...