search for: temp5

...;temp19", "temp19", "temp19", "temp2", "temp2", "temp2", "temp2", "temp2", "temp20", "temp20", "temp20", "temp3", "temp3", "temp3", "temp4", "temp5", "temp6", "temp6", "temp6", "temp6", "temp7", "temp7", "temp7", "temp7", "temp8", "temp8", "temp8", "temp8", "temp8", "temp9", "temp1",...

...r of time series) when I have only one column? Why is the number of an object of only one object "NULL"? It should be one, shouldn't it? (The following example does not involve the creation of a zoo object; in reality, similar problems are encountered when I create a zoo object) > temp5<-read.csv("A_Consumption.csv", header=TRUE)> temp5[1:3,] TIME C C_D C_ND 1 196101 70345 1051 69294 2 196102 61738 905 60833 3 196103 63838 860 62978> temp6<-temp5[,2:ncol(temp5)]> temp6[1:3,] C C_D C_ND 1 70345 1051 69294 2 61738 905 60833 3 63838 860 6297...

...; z1 > > 1 0.8414710 > 2 0.9092974 > 3 0.1411200 > 4 -0.7568025 > R> dim(z1) > [1] 4 1 > > R> dim(z) <- c(NROW(z), NCOL(z)) > R> z > > 1 0.8414710 > 2 0.9092974 > 3 0.1411200 > 4 -0.7568025 > R> dim(z) > [1] 4 1 > > > temp5<-read.csv("A_**Consumption.csv", header=TRUE)> temp5[1:3,] TIME >>> C C_D C_ND >>> >> 1 196101 70345 1051 69294 >> 2 196102 61738 905 60833 >> 3 196103 63838 860 62978> temp6<-temp5[,2:ncol(temp5)]> temp6[1:3,] >> C C_...

Hello all, I am trying to understand how to specify nested factors when using coxph(), and if it is appropriate to nest these factors in my situation. In the simplest form, I am testing two different temperatures, with each temperature being performed twice in different experimental periods (e.g. Temp5 performed in Period A and C, Temp4 performed in Period B and D) I am trying to see if survival time is affected by the treatment temperature. To do this I am using temperature and experimental period nested within temperature as factors. > LOEtempmod.5days=coxph(LOE.stable.5days~Temp+Temp/Peri...

output of *dovecot --version*: Dovecot version : 2.2.9 ----- output of *doveconf -n:* auth_debug = yes > > auth_mechanisms = plain login > > auth_verbose = yes > > disable_plaintext_auth = no > > mail_debug = yes > > mail_location = > maildir:/var/mail/vhosts/%d/%n:LAYOUT=fs:DIRNAME=dovecot_maildir > > mail_plugins = " mail_log notify mail_filter"

...' to further covert to LPSTR const char* comLine; int n = commandLine.GetLength(); comLine = commandLine.GetBuffer(n); // Start the child process. if( !CreateProcess(NULL, //Example "\"JPSecWin32\\jpsec.exe\" -i .\\..\\..\\JPSecWin32\\lenna_enc.jp2 -o .\\..\\..\\JPSecWin32\\temp5.jp2 -k .\\..\\..\\JPSecWin32\\keys.txt -dec", // No module name (use command line). LPSTR(comLine), // Command line. NULL, // Process handle not inheritable. NULL, // Thread handle not inheritable. FALSE, // Set handle inheritance to FALSE. 0, // No creation flags. NULL, // Use parent...

...r, I have tried using the 'lm' function and i get the result, like this. ( 'xi' is 25 by 1 vector ) > reg <- lm(xi~temp) > > reg Call: lm(formula = xi ~ temp) Coefficients: (Intercept) temp1 temp2 temp3 temp4 temp5 temp6 temp7 -3.704e-15 2.434e-02 4.087e-02 NA -5.241e-01 -1.213e-02 NA -1.960e-02 temp8 temp9 temp10 temp11 temp12 temp13 temp14 temp15 6.516e-03 NA -6.651e-02 8.865e-02...

I'm wondering if anyone has written some functions or code for handling very large files in R. I am working with a data file that is 41 variables times who knows how many observations making up 27MB altogether. The sort of thing that I am thinking of having R do is - count the number of lines in a file - form a data frame by selecting all cases whose line numbers are in a supplied vector