The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
This package executes simple parametic models for right-censored survival data. Functionality emulates capabilities in Minitab, including fitting right-censored data, assessing fit, plotting survival functions, and summary statistics and probabilities.
You can install parmsurvfit from github with:
# install.packages("devtools")
devtools::install_github("apjacobson/parmsurvfit")library(parmsurvfit)Fitting data and assessing fit:
fit_data(data = firstdrink, dist = "weibull", time = "age")
#> Fitting of the distribution ' weibull ' on censored data by maximum likelihood
#> Parameters:
#> estimate
#> shape 2.536106
#> scale 19.684061
plot_density(data = firstdrink, dist = "weibull", time = "age")
plot_ppsurv(data = firstdrink, dist = "weibull", time = "age")
compute_AD(data = firstdrink, dist = "weibull", time = "age")
#> [1] 315.5693Survival functions:
plot_surv(data = firstdrink, dist = "weibull", time = "age")
plot_haz(data = firstdrink, dist = "weibull", time = "age")
plot_cumhaz(data = firstdrink, dist = "weibull", time = "age")
Summary statistics and probabilities:
surv_prob(data = firstdrink, dist = "weibull", x = 30, lower.tail = F, time = "age")
#> P(T > 30) = 0.05439142
surv_summary(data = firstdrink, dist = "weibull", time = "age")
#> shape 2.536106
#> scale 19.68406
#> Log Liklihood -3170.779
#> AIC 6345.557
#> BIC 6355.373
#> Mean 17.47135
#> StDev 7.380763
#> First Quantile 12.04374
#> Median 17.03536
#> Third Quantile 22.38974These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.