# Journal of Statistical Theory and Practice

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 87-99

*U*-statistic of order (1,1). Its variance can be written out as a sum of three tractable covariances. It is then possible to consider each of these covariances as

*U*-statistics themselves and follow the

*U*-statistics formalism to derive their unbiased estimates. Over the years, alternative methods...

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 73-86

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 202-215

*k*,...

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 133-153

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 216-225

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 226-238

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 1-6

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 20-39

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 7-19

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 121-132

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 40-58

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 179-201

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 100-120

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 59-72

*p*values of statistical models for count data arising in Box-Behnken designs. The statistical model we consider is a discrete version of the first-order model in the response surface methodology. For our models, the Markov basis, a key notion to construct a connected Markov chain on a given sample space, is characterized as generators...

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 154-178

Journal of Statistical Theory and Practice > 2016 > 10 > 2 > 444-455

Journal of Statistical Theory and Practice > 2016 > 10 > 2 > 456-471

Journal of Statistical Theory and Practice > 2016 > 10 > 2 > 389-404

*a*in the symmetric stable Lévy process $$L_t^\delta $$ with the parameter of stability

*δ*∈ (0, 2] with a deterministic drift $$Y_t^\delta = ad(t) + L_t^\delta $$ , there are some simple options how to do it. We may, for example, base this inference on the properties of the stable distribution. Although this method is very simple, it turns...

Journal of Statistical Theory and Practice > 2016 > 10 > 2 > 405-419

Journal of Statistical Theory and Practice > 2016 > 10 > 2 > 420-443