I have attempted to install the packages Rtools and rgrs but the
install.packages command yields a message that the same are not available
for R version 4.0.
How do i get around this as i need the said packages to implement some
credit scoring GLMs using the " rgrs" package.
With Regards,
Char
Dear Sirs,
The below listed code fits a gamma and a pareto distribution to a data set
danishuni. However the distributions are not appropriate to fit both tails
of the data set hence a mixed distribution is required which has ben
defined as "mixgampar"
as shown below.
library(fitdistrplus)
x<-
Dear Sirs,
I have a data frame that has a column that shows the transaction date.
How do i add another column that extracts the year of transaction from the
transaction date.
Charles
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R-help@r-project.
I have the following glm
v_glm <-
glm(claim_count~ave_age+cost+inc.count+p.statcount,data=v,family=poisson)
claim_count - dependent variable and is discrete
ave_age - predictor variable and is continuous
cost - predictor variable and is continuous
inc_count - predictor variable and is discret
I have a data frame whose rows are 678013 . I would like to remove rows
from 30696 to 678013 and then attach a new column with a length of 30595.
I tried
Y<- X[-30595:678013,] and its not working
In addition how do i add a new column
Kindly assist.
Charles
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am running a glm to model the number of accidents that result from diesel
or petrol cars.
How can i run a glm that on only one factor i.e. diesel only.
require(CASdatasets)
data(freMTPL2freq)
CONTRACTS<-
data.frame(freMTPL2freq$IDpol,freMTPL2freq$ClaimNb,freMTPL2freq$Exposure,freMTPL2freq$V
# i run the following after fitting claims data into the negative binomial
as the frequency distribution and the lognormal for the severity
distribution using the package "fitdistrplus".
require(actuar)
fx<- discretize(plnorm(x,11.69,0.79331),method="unbiased",step=500,from=0,
to=qln
I have just installed R 3.1.1 in a machine where R 3.0.1 is already
installed. Is it possible to use packages in the 3.0.1 on the 3.1.1.
version as the same are in a single workstation.
Charles
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# I have a daily series of count of transactions data i want to decompose
and forecast.
d<-c(723, 772, 967, 897, 621, 684, 722, 764, 856, 819,
678, 708, 698, 832, 928, 834, 649, 676, 635, 729, 778, 817, 616,
598, 605, 851, 822, 791, 678, 703, 716, 834, 872, 831, 641, 610,
699, 840, 901, 789, 620,
I have a data set with daily claim numbers. I group with monthly totals and
create a time series as follows
v.ts<- ts(v, start=2008,frequency=12)
How can the daily data be converted into a time series where there is no
claim number for sundays and public holidays.
Charles.
[[alternati
require(copula)
# I specify the copula
gmb<-gumbelCopula(4,dim=2)
# The bivariate CDF is generated
myCDF<-mvdc(gmb,margins=c("lnorm","nbinom"),paramMargins=list(list(meanlog=11.69,sdlog=0.7781),list(mu=16,size=2.6)))
# A random sample of the bivariate risk data is generated as a matrix.
Th
Hello,
I was attempting to install the package opVAr and got the following message
Warning message:
package '' is not available (for R version 3.0.2)
Is this package available at all.
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require(copula)
# I specify the copula
gmb<-gumbelCopula(4,dim=2)
# The bivariate CDF is generated
myCDF<-mvdc(gmb,margins=c("lnorm","nbinom"),paramMargins=list(list(meanlog=11.69,sdlog=0.7781),list(mu=16,size=2.6)))
# A random sample of the bivariate risk data is generated as a matrix.
Th
# I define a bivariate copula composed of 2 marginals each with 2 parameters
gmb<-gumbelCopula(4,dim=2)
# Idefine the bivariate CDF specifying the already fitted parameters
from the log normal and negative binomial
myCDF<-mvdc(gmb,margins=c("lnorm","nbinom"),paramMargins=list(list(meanlog=11.6
I have been trying to fit a time series object using the garchFit()
function. However am getting the results below
> class(v.ts)
[1] "ts"
fit=garchFit(v.ts)
Error in if (allVarsTest != 1) { : missing value where TRUE/FALSE needed
I do not understand the error. Which missing value is required. K
I have monthly claims data from 2009 to end of 2013 and would like to
forecast for 2014. How is this done in R.
Charles.
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PLE
I was attempting to install the ts package for time series analysis but
got the following message.
Warning message:
package is not available (for R version 3.0.2)
Charles.
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Hi,
I had downloaded the package zoo under R version 3.0.0. Afterwards i
downloaded R version 3.0.2 on the same workstation. Is it possible to use
the zoo package from 3.0.0. in 3.0.2.
Is is possible to upgrade from version 3.0.1 to 3.0.2 for example without
downloading afresh and retain the
what is the purpose of the subject function
Charles
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.h
> require(MASS)
> n<- 10
> n
[1] 1e+05
> w<- rgamma(n,rate=0.5,shape=5);head(w)
[1] 14.135679 18.839336 6.623502 17.165505 2.847572 7.511726
> fit.w<- fitdistr(w,"weibull")
Warning messages:
1: In densfun(x, parm[1], parm[2], ...) : NaNs produced
2: In densfun(x, parm[1], parm[2], ...) : NaN
I have sales data for years 2011, 2012 and upto september 2013. I have
applied the decompose function to filter the trend , seasonal and random
component. however i would like to apply the predict function to forecast
the sales for the rest of year and into 2014. How can i establish the order
of t
I have been copying graphs as bitmap image from R by right clicking on
them and pasting on word. However this does not seem to be working any
more. Is there another way.
Charles
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How can a person in a controlled environment install additional R
packages..
Charles.
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PLEASE do read the posting guide http:
v<- read.csv(file="sales.csv",header=TRUE)
v
i get an output whose column names are V1,V2, and so on but i would like to
retain the original column names such as january through to december.
Charles.
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After reading a data set from excel into R it is of the type list. How can
such a list be converted into a data frame so as to attach the columns.
Charles.
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how can one read data from MSEXcel into R especially in a case where one
does not have administrator rights to install additional packages. In short
how to read data from MSExcel into R with base packages only.
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I run the following:
library(actuar)
x <- seq(0, 22, 0.5)
fl <- discretize(plnorm(x, 2.1), from = 0, to = 22, step = 0.5, method
="lower")
Fs <- aggregateDist("recursive", model.freq = "poisson",model.sev = fl,
lambda = 10, x.scale = 0.5)
Warning message:
In panjer(fx = model.sev, dist = dist, p0 =
I run the following in the "actuar" package while trying to discretize the
lognormal distribution which i had fitted using the "fitdistrplus" package.
fx <- discretize(plnorm(11.69,2.1),from = 0, to = 22, step = 0.5, method =
"upper")
Error in discretize(plnorm(11.69, 2.1), from = 0, to = 22, st
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