[R] counting process and output of survfit
Hello, I put my data in conditional counting process format basically by adding a stratum variable to distinguish between observations. I fit a model and then used survfit function. These are the first five lines of output. time n.risk n.event survival std.err lower 95% CI upper 95% CI 849 11 1 9.22e-01 7.53e-02 7.85e-01 1.00 3025 28 1 8.91e-01 7.87e-02 7.50e-01 1.00 3089 28 1 8.62e-01 8.14e-02 7.16e-01 1.00 4691 37 1 8.39e-01 8.23e-02 6.92e-01 1.00 5295 43 1 8.21e-01 8.26e-02 6.74e-01 0.999566 My questions: 1. How does it determine n.risk at time t? 2. How does it calculate the survival at the end of time t? thank you! [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Estimating error rate for a classification tree
Hi, I created an rpart object and pruned the tree using 1-SE rule. I used 10-fold cross validation while creating the tree. Then, I extracted the cross-validated predictions for my data points using xpred.rpart and obtained some statistics like precision, recall, overall error rate, etc. However, these values change each time I run xpred.rpart because of the random shuffling going on before cross validation (I think so). What should I do in this case? I am inclined to treat them as random variables with normal distribution. So, when I have, say 100 runs, i can say something about the mean with some confidence interval. However, I also doubt that these subsequent runs may not be independent from each other. I would highly appreciate if someone could make a suggestion. Best regards __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Probability plotting with R
Hello, Our professor asked us to do probability plotting using weibull paper, exponential paper, normal, log-normal paper, etc. I know I can create Q-Q plot for normal dist. and see if all te points are on one line. How do I go about other distributions? I tried generating different samples and use the general qq function. However, I could not do it since I don't know the population parameters (In normal QQ, we assume that the sample mean and variance were population parameters too) I was wondering if there is any way of probability plotting with R instead of using the papers. I appreciate your helps in advance. Regards A. Gunes Koru __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
