Computational Statistics (Journal)

A Bibliography of the Journal of Computational and Graphical Statistics

Accelerating [HHC03]. acceleration [GS94]. Accept [CR98]. Accept-Reject [CR98]. Access [SH03]. Accompaniment [Rap01]. Accounting [HDM02]. Accurate [CJ02]. Acoustic [BMO01]. Adaptive [Bil00, DZ99, EHW03, GK97, Gou98, Gri99, MS03, Oeh98, PTP03, Pit02, Zha97]. Additive [EM02, KLH99, OR99, ST99]. Adjusted [DIR02]. After [Hub99]. Aided [HIT99]. Akaike [ST99]. Algorithm [CB01, CCFM01, GJ97, Glu00, HL...

Computational rank-based statistics

This review discusses two algorithms which can be used to compute rank-based regression estimates. For completeness, a brief overview of rank-based inference procedures in the context of a linear model is presented. The discussion includes geometry, estimation, inference, and diagnostics. In regard to computing the rank-based estimates, we discuss two approaches. The first approach is based on ...

Computational Statistics Spring 2008

Computational Methods in Statistics

Appendix to “ Bayesian Mixtures of Autoregressive Models ” published in the Journal of Computational and Graphical Statistics

j=1 |X ′ pZjXp + c−1X ′ pXp|b −aj j , where Zj = diag(ztjpr, t = P + 1, . . . , n). Note that ztjpr takes on the same value (zero or one) for all t ∈ {1 + (s − 1)L, . . . , sL}. The expressions for aj and bj are aj = 1 2 ∑n t=P+1 zjtpr + α and bj = 1 2 yMjy ∗ + β, where Mj = Zj − ZjXp(X ′ pZjXp + c−1X ′ pXp) −1X ′ pZj. 3. Let psjpr = sL ∏ t=1+(s−1)L p(yt|xt−1;φjpr, σ jpr). Draw the indicators f...