Liburu elektroniko honi buruz
Assume one has to estimate the mean J x P( dx) (or the median of P, or any other functional t;;(P)) on the basis ofi.i.d. observations from P. Ifnothing is known about P, then the sample mean is certainly the best estimator one can think of. If P is known to be the member of a certain parametric family, say {Po: {) E e}, one can usually do better by estimating {) first, say by {)(n)(.~.), and using J XPo(n)(;r.) (dx) as an estimate for J xPo(dx). There is an "intermediate" range, where we know something about the unknown probability measure P, but less than parametric theory takes for granted. Practical problems have always led statisticians to invent estimators for such intermediate models, but it usually remained open whether these estimators are nearly optimal or not. There was one exception: The case of "adaptivity", where a "nonparametric" estimate exists which is asymptotically optimal for any parametric submodel. The standard (and for a long time only) example of such a fortunate situation was the estimation of the center of symmetry for a distribution of unknown shape.
Baloratu liburu elektroniko hau
Eman iezaguzu iritzia.
Irakurtzeko informazioa
Telefono adimendunak eta tabletak
Instalatu Android eta iPad/iPhone gailuetarako Google Play Liburuak aplikazioa. Zure kontuarekin automatikoki sinkronizatzen da, eta konexioarekin nahiz gabe irakurri ahal izango dituzu liburuak, edonon zaudela ere.
Ordenagailu eramangarriak eta mahaigainekoak
Google Play-n erositako audio-liburuak entzuteko aukera ematen du ordenagailuko web-arakatzailearen bidez.
Irakurgailu elektronikoak eta bestelako gailuak
Tinta elektronikoa duten gailuetan (adibidez, Kobo-ko irakurgailu elektronikoak) liburuak irakurtzeko, fitxategi bat deskargatu beharko duzu, eta hura gailura transferitu. Jarraitu laguntza-zentroko argibide xehatuei fitxategiak irakurgailu elektroniko bateragarrietara transferitzeko.
