Počet záznamov: 1
Multinomial and empirical likelihood under convex constraints
SYS 0250323 LBL ---naa--22--------450- 005 20231206095651.0 014 $a 000408006600075 $2 WOS CC. SCIE 014 $a 000408006600075 $2 CCC 014 $a 2-s2.0-85021629022 $2 SCOPUS 017 70
$a 10.1214/17-EJS1294 $2 DOI 100 $a 20170907 2017 m y slo 03 ba 101 0-
$a eng 102 $a US 200 1-
$a Multinomial and empirical likelihood under convex constraints $e directions of recession, Fenchel duality, the PP algorithm $f Marian Grendár, Vladimír Špitalský 330 $a The primal problem of multinomial likelihood maximization restricted to a convex closed subset of the probability simplex is studied. A solution of this problem may assign a positive mass to an outcome with zero count. Such a solution cannot be obtained by the widely used, simplified Lagrange and Fenchel duals. Related flaws in the simplified dual problems, which arise because the recession directions are ignored, are identified and the correct Lagrange and Fenchel duals are developed. 463 -1
$1 001 umb_un_cat*0293257 $1 011 $a 1935-7524 $1 200 1 $a Electronic Journal of Statistics $v Vol. 11, no. 1 (2017), pp. 2547-2612 $1 210 $a [Shaker Heights] $c Institute of Mathematical Statistics $d 2017 606 0-
$3 umb_un_auth*0186299 $a contingency tables 606 0-
$3 umb_un_auth*0035842 $a lineárne modely $X linear models 606 0-
$3 umb_un_auth*0142965 $a estimating equations 615 $n 51 $a Matematika 675 $a 51 700 -0
$3 umb_un_auth*0015446 $a Grendár $b Marian $9 50 $f 1969- $4 070 701 -1
$3 umb_un_auth*0097800 $a Špitalský $b Vladimír $p UMBFP10 $4 070 $9 50 $f 1973- $T Katedra matematiky 801 -0
$a SK $b BB301 $g AACR2 $9 unimarc sk T85 $x existuji fulltexy
Počet záznamov: 1