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Differential Geometrical Theory of Statistics
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Entropy2016,18, 421 0.0 0.2 0.4 0.6 0.8 1.0 N = 50, nominal level = 0.1 πc 0.00 0.05 0.10 0.15 0.20 0.0 0.2 0.4 0.6 0.8 1.0 N = 50, nominal level = 0.05 πc 0.00 0.02 0.04 0.06 0.08 0.10 Figure8.Heatmapof theactual levelof the test forN=50atnominal levels0.1and0.05; thestandard rule-of-thumb(whereexpectedcountsaregreater than5)applies inside theclosedblackcurvedregion. 5.Discussion Thispaperhas illustrated thekey importanceofworkingwith theboundaryof theclosureof exponential familieswhenstudyinggoodness-of-ïŹt testing in thehighdimensional, lowsamplesize context. Someof thiswork isnew(Section2),whilesomeuses thestructureofextendedexponential families toaddinsight tostandardresults in the literature (Section3). The last section,Section4,uses simulationstudies tostart toexploreopenquestions in thisarea. Oneopenquestion—relatedto theresultsofTheorems1and2—is tosee ifauniïŹedtheory, forall valuesofα, andover largeclassesofextendedexponential families, canbedeveloped. Acknowledgments:Theauthorswould like to thanktheEPSRCfor thesupportofgrantnumberEP/L010429/1. GermainVanBeverwouldalso like to thankFRS-FNRSfor its support throughthegrantFC84444.Wewouldalso like to thankthereferees forveryhelpfulcomments. AuthorContributions: All fourauthorsmadecritical contributions to thepaper. R.S.madekeycontribution to,especially,Section4. P.M.andF.C.providedtheoverall structureandkeycontentdetailsof thepaper.G.V.B. providedinvaluablesuggestions throughout. ConïŹ‚ictsof Interest:TheauthorsdeclarenoconïŹ‚ictsof interest. AppendixA. ProofofTheorem1 Westartbynotinganimportant recurrencerelationwhichwillbeexploited in thecomputations below.BydeïŹnition, forany t :=(ti)∈Rk+1,n=(ni)hasmomentgeneratingfunction M(t;N) :=E{exp(tTn)}=[m(t)]N withm(t)=∑ki=0ai and ai= ai(ti)=πie ti. Putting fN,i(t;r) :=N(r) [m(t)] N−r ari (0≀ r≀N), where N(r) := NPr= { 1 if r=0 N(N−1)...(N−(r−1)) if r∈{1,...,N} , wehave M(t;N)= fN,i(t;0) (0≀ i≀ k) (A1) andtherecurrencerelation: ∂fN,i(t;r) ∂ti = fN,i(t;r+1)+rfN,i(t;r) (0≀ i≀ k; 0≀ r<N) . (A2) 337
zurĂŒck zum  Buch Differential Geometrical Theory of Statistics"
Differential Geometrical Theory of Statistics
Titel
Differential Geometrical Theory of Statistics
Autoren
Frédéric Barbaresco
Frank Nielsen
Herausgeber
MDPI
Ort
Basel
Datum
2017
Sprache
englisch
Lizenz
CC BY-NC-ND 4.0
ISBN
978-3-03842-425-3
Abmessungen
17.0 x 24.4 cm
Seiten
476
Schlagwörter
Entropy, Coding Theory, Maximum entropy, Information geometry, Computational Information Geometry, Hessian Geometry, Divergence Geometry, Information topology, Cohomology, Shape Space, Statistical physics, Thermodynamics
Kategorien
Naturwissenschaften Physik
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Differential Geometrical Theory of Statistics