search for: smedian

Displaying 4 results from an estimated 4 matches for "smedian".

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2006 Feb 03
0
Cause of Error 1:nrow(X) : argument NA / NaN
Dear R Helpers I am trying to get function smedian.hilow to work using Hmisc summarize on variable conc in dataframe pkindivmtd by time and dose using: attach(pkindivmtd) sconc <- summarize(conc,llist(time,dose),smedian.hilow) I get the error message Erreur dans 1:nrow(X) : argument NA / NaN Contents of pkindivmtd is > contents(pkindivm...
2005 May 13
5
Conflict between xtable and Hmisc when using Sweave?
...E,echo=FALSE>>= # library(xtable) library(Hmisc) set.seed(111) dfr <- expand.grid(month=1:12, year=c(1997,1998), reps=1:100) month <- dfr$month year <- dfr$year y <- abs(month-6.5) + 2*runif(length(month)) + year-1997 s <- summarize(y, llist(month,year), smedian.hilow, conf.int=.5) print(xYplot(Cbind(y,Lower,Upper) ~ month, groups=year, data=s, keys='lines', method='alt', type='b')) @ \end{center} \end{figure} \end{document} ************************ > version _ platform i686-pc-linux-gnu arch i686...
2007 Apr 24
0
Bug in xYplot() with method = 'filled bands'
...artiles. The outer quartiles are # displayed using "filled bands" set.seed(111) dfr <- expand.grid(month=1:12, year=c(1997,1998), reps=1:100) month <- dfr$month; year <- dfr$year y <- abs(month-6.5) + 2*runif(length(month)) + year-1997 s <- summarize(y, llist(month,year), smedian.hilow, conf.int=.5) # filled bands: default fill = pastel colors matching solid colors # in superpose.line (this works differently in R) xYplot ( Cbind ( y, Lower, Upper ) ~ month, groups=year, method="filled bands" , data=s, type="l") The comment "this works differ...
2007 Jun 16
2
Visualize quartiles of plot line
Hello, I'm currently using a simple plot to visualize some mean values. I'm having ~200 datapoints on the x-axis, each has 10 records. I'm currently plotting only the mean value of each of the datapoints. What I need is a way to visualize the quartiles/error/whatever of these points. I thought about boxplots, but I have to many points on the xaxis - it would be impossible to see