I have tried to fit several distributions to my continuous data (Pareto, Log-normal, Exponential, Gamma). The distribution of data is given below.
I used Kolmogorov-Smirnov test to compare my data to generated distributions using estimated parameters from
fitdistr function using the following code:
fit<-fitdistr(mydata,"gamma")$estimate gamma.generated = rgamma(length(mydata),fit,fit) w = ks.test(mydata,gamma.generated) Two-sample Kolmogorov-Smirnov test D = 0.089, p-value < 2.2e-16 alternative hypothesis: two-sided
However, I always get p-value < 0.001 for all distributions and a warning message "p-value will be approximate in the presence of ties". Does this mean that my data are not from any of these distributions or the test is too sensitive to some values? What would be other options (i.e. tests) that I can try? Thanks.