PPT-Pertemuan 4,5 Estimasi Parameter Model Regresi

Pengujian Hipotesis dan Interval Konfidensi Dosen Pengampu MK Dr Idah Zuhroh MM Evellin D Lusiana SSi MSi EKONOMETRIKA Materi Estimasi parameter regresi linier sederhana OLS Asumsiasumsi OLS. This is useful only in the case where we know the precise model family and parameter values for the situation of interest But this is the exception not the rul e for both scienti64257c inquiry and human learning inference Most of the time we are in Parameter . R. edundancy . in . Ecological . State-Space . M. odels. Diana . Cole . and . Rachel . McCrea . National Centre for Statistical Ecology, University of . Kent. Lapwing Example. Lapwing (. Vanellus. Diana Cole, NCSE, University of Kent. Rémi Choquet, . Centre d'Ecologie Fonctionnelle et Evolutive. Ben Hubbard, NCSE, University of Kent. Introduction – Example Capture-Recapture. Herring Gulls (. Diana Cole. University of Kent. A model is parameter redundant (or non-identifiable) if you cannot estimate all the parameters.. Caused by the model itself (intrinsic parameter redundancy).. Caused . Parameter . R. edundancy . in . Integrated Population Models. Diana . Cole . and . Rachel . McCrea . National Centre for Statistical Ecology, University of . Kent. Lapwing Example. Lapwing (. Vanellus. Parameter . R. edundancy . in . Integrated Population Models. Diana . Cole . and . Rachel . McCrea . National Centre for Statistical Ecology, . School of Mathematics, Statistics and Actuarial Science, University . KANSAS. OR . OZ. In class:. Mary C. Hill U.S. Geological Survey, Boulder. . Olda. . Rakovec. . Wageningen. University, Netherlands. Other co-authors:. . Martyn. Clark UCAR, Boulder. Bayesian Hierarchical Model (BHM). Ralph F. Milliff. ; CIRES, University of Colorado. Jerome . Fiechter. , Ocean Sciences, UC Santa . Cruz. Christopher K. . Wikle. , Statistics, University of Missouri. of . Aurick. . Qiao. , Joseph Gonzalez, Wei Dai, and . Jinliang. Wei). Parameter Servers. 1. Regret analysis for on-line optimization. RECAP. 2. 2009. RECAP. 3. Take a gradient step: . x’ = . x. Bayesian Hierarchical Model (BHM). Ralph F. Milliff. ; CIRES, University of Colorado. Jerome . Fiechter. , Ocean Sciences, UC Santa . Cruz. Christopher K. . Wikle. , Statistics, University of Missouri. Madan Musuvathi. . Visiting Professor, UCLA . Principal Researcher, Microsoft Research. Course Project. Write-ups due June 1. st. Project presentations . 12 presentations, 10 mins each, 15 min slack. in . Integrated Population Models. Diana . Cole . and . Rachel . McCrea . National Centre for Statistical Ecology, . School of Mathematics, Statistics and Actuarial Science, University . Models. Diana Cole, University of Kent. Rémi. . Choquet. , CEFE, CNRS, France.. x. Occupancy Model example. Parameters. : . – species is detected. .. C. an . only estimate . rather than . and . . of. batch . polymerization. . processes. Student: Fredrik Gjertsen. Supervisor, NTNU: Prof. Sigurd . Skogestad. Supervisor, . external. : Peter Singstad, . Cybernetica. AS. State and parameter .