عنوان

Calibrando Niveles de Signifancia y p-Valores en Modelos Lineales

شماره

TL51499

زبان متن نوشتاري يا گفتاري و مانند آن

انگلیسی

عنوان اصلي

Calibrando Niveles de Signifancia y p-Valores en Modelos Lineales

نام عام مواد

[Thesis]

نام نخستين پديدآور

Vélez Ramos, Daiver De Jesús

نام ساير پديدآوران

Pericchi Guerra, Luis Raul

نام ناشر، پخش کننده و غيره

University of Puerto Rico, Rio Piedras (Puerto Rico)

تاریخ نشرو بخش و غیره

2019

متن يادداشت

101 p.

جزئيات پايان نامه و نوع درجه آن

Ph.D.

کسي که مدرک را اعطا کرده

University of Puerto Rico, Rio Piedras (Puerto Rico)

امتياز متن

2019

متن يادداشت

We put forward an adaptive alpha for hypothesis tests in which linear nested models are compared which changes with the amount of sample information. This calibration may be interpreted as a Bayes-non-Bayes compromise, and leads to statistical consistency. Moreover, we prove that the Robust Lower Bound proposed by Sellke et al. is a valid p-value in the sense of Casella and Berger. Using this lower bound we build a calibration of p values for selecting nested linear models, the "p Posterior Probability Linear" (pPPL) which maps p values into approximations of posterior probabilities taking into account the effect of sample sizes. This calibration is based on Pericchi and Pérez and we present several illustrations from where it is apparent that the pPPL closely approximates exact objective Bayes Factors. In particular, it has the same properties asymptotic as posterior probabilities but avoiding the problems of "Bayesian Information Criterion" (BIC) for small samples relative to the number of parameters.

اصطلاح موضوعی

Mathematics

اصطلاح موضوعی

Science education

مستند نام اشخاص تاييد نشده

Vélez Ramos, Daiver De Jesús

مستند نام اشخاص تاييد نشده

Pericchi Guerra, Luis Raul

مستند نام تنالگان تاييد نشده

University of Puerto Rico, Rio Piedras (Puerto Rico)

نام الکترونيکي

فرمت انتشار

p

نوع ماده

[Thesis]

کد کاربرگه

276903

سطح دسترسي

a

تكميل شده

Y