305,463 research outputs found
A Quasi likelihood approximation of posterior distributions for likelihood-intractable complex models
No full textComplex models typically involve intractable likelihood functions which, from a Bayesian perspective, lead to intractable posterior distributions. In this context, Approximate Bayesian computation (ABC) methods can be used in order to obtain a valid posterior
approximation. However, when simulation from the model is computationally demanding, then the ABC approach may be cumbersome. We discuss an alternative method, where the intractable likelihood is approximated by a quasi-likelihood calculated through an algorithm that is reminiscent of the ABC. The proposed approximation method requires less computational effort than ABC. An extension to multiparameter models is also considered and the method is illustrated by several examples
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Objective Bayesian inference with proper scoring rules
No full textStandard Bayesian analyses can be difficult to perform when the full likelihood, and consequently the full posterior distribution, is too complex or even impossible to specify or if robustness with respect to data or to model misspecifications is required. In these situations, we suggest to resort to a posterior distribution for the parameter of interest based on proper scoring rules. Scoring rules are loss functions designed to measure the quality of a probability distribution for a random variable, given its observed value. Important examples are the Tsallis score and the Hyvärinen score, which allow us to deal with model misspecifications or with complex models. Also the full and the composite likelihoods are both special instances of scoring rules. The aim of this paper is twofold. Firstly, we discuss the use of scoring rules in the Bayes formula in order to compute a posterior distribution, named SR-posterior distribution, and we derive its asymptotic normality. Secondly, we propose a procedure for building default priors for the unknown parameter of interest that can be used to update the information provided by the scoring rule in the SR-posterior distribution. In particular, a reference prior is obtained by maximizing the average α-divergence from the SR-posterior distribution. For 0≤|α|<1, the result is a Jeffreys-type prior that is proportional to the square root of the determinant of the Godambe information matrix associated with the scoring rule. Some examples are discussed
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Bayesian Inference for directional data through ABC and homogeneous proper scoring rules
No full text
Author, publisher and bookseller : a tripartite synergy in Nigerian book industry
No full textThis work is about the roles of Author, Publisher and Bookseller in Book development in
Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after
which it proceeded by defining who an author, a publisher, and a bookseller is and
expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in
the emerging Information Society. Furthermore, the various constraints to book
development were identified while the paper advised on how the Book Industry can be
further promoted in Nigeria. However, the paper concluded and made recommendations
on how the Book sector can help in enhancing scholarship in the country
PENGGUNAAN MEDIA EDUCANDY BASED E-LEARNING DALAM MENINGKATKAN MOTIVASI BELAJAR SISWA PADA MATA PELAJARAN AKIDAH AKHLAK DI MAN 5 BOJONEGORO
No full textPenelitian ini berjudul “Penggunaan Media Educandy Based E-Learning Dalam Meningkatkan Motivasi Belajar Siswa Pada Mata Pelajaran Aqidah Akhlak di MAN 5 Bojonegoro” Penelitian ini ditulis oleh RULI MARDIANA, NIM 210101258, Prodi Pendidilan Agama Islam, Fakultas Tarbiyah, Universitas Nahdlatul Ulama Sunan Giri Bojonegoro. Latar Belakang Penulis melakukan penelitian ini permasalahan yang sering ditemui dilokasi penelitian yaitu bagaimana cara meningkatkan motivasi belajar siswa di MAN 5 Bojonegoro dan bagaimana pengaruh dalam meningkatkan motivasi belajar siswa di MAN 5 Bojonegoro. Kemudian penelitian ini bertujuan untuk mengetahui bagaimana cara meningkatkan motivasi belajar siswa dan sepengaruh apa jika pembelajaran menggunakan media educandy Based E-Learning. Penelitian ini menggunakan pendekatan kuantitatif dengan desain one group pre-test-post-test. Sampel 22 siswa kelas XI Agama. Data dikumpulkan melalui hasil pre-test-post-test.
Metode penelitian yang digunakan ini adalah penelitian kuantitatif dengan rancangan penelitian pre-eksperimen design dengan bentuk one group pre test- post test design. Dengan menggunakan pengumpulan data berupa instrument Motivasi Instrinsik,Motivasi Ekstrinsik, keterlibatan belajar, efikasi diri, hasil pembelajaran, sikap terhadap media. Penelitian ini melibatkan sejmlah 22 siswa di kelas XI Agama sebanyak 2 kali pertemuan. Analisi data yang digunakan yaitu uji normalitas shapiro wilk, dan uji paired sample t-test.
Berdasarkan uji paired sample t-test diketahui nilai signifikan (2 tailed) sebesar 0,000 < 0,05 maka menunjukkan H0 ditolak dan Ha diterima yang artinya terdapat perbedaan yang signifikan antara sebelum dan sesudah menggunakan media Educamdy. Maka dapat disimpulkan bahwa penelitian based e-learning ini berpengaruh positif untuk meningkatkan motivasi belajar siswa
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