Stochastic Restricted Two-Parameter Maximum Likelihood Estimator in Binary Logistic Regression Model

2020 ◽  
Vol 09 (04) ◽  
pp. 515-524
Author(s):  
媛 邹
Keyword(s):  
Logistic Regression ◽  
Maximum Likelihood ◽  
Regression Model ◽  
Maximum Likelihood Estimator ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Likelihood Estimator ◽  
Binary Logistic Regression Model ◽  
Two Parameter

scholarly journals ESTIMATION OF THE BINARY LOGISTIC REGRESSION MODEL PARAMETER USING BOOTSTRAP RE-SAMPLING

2018 ◽  
Vol 48 (3) ◽  
pp. 199-204 ◽  
Author(s):  
R. LI ◽  
J. ZHOU ◽  
L. WANG
Keyword(s):  
Logistic Regression ◽  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Parametric Bootstrap ◽  
Binary Logistic Regression Model ◽  
Bayesian Bootstrap ◽  
Non Parametric

In this paper, the non-parametric bootstrap and non-parametric Bayesian bootstrap methods are applied for parameter estimation in the binary logistic regression model. A real data study and a simulation study are conducted to compare the Nonparametric bootstrap, Non-parametric Bayesian bootstrap and the maximum likelihood methods. Study results shows that three methods are all effective ways for parameter estimation in the binary logistic regression model. In small sample case, the non-parametric Bayesian bootstrap method performs relatively better than the non-parametric bootstrap and the maximum likelihood method for parameter estimation in the binary logistic regression model.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI PEROLEHAN KREDIT OLEH PENGUSAHA MIKRO

2018 ◽  
Vol 4 (3) ◽  
Author(s):  
Abdul Azis Safii ◽  
Tri Suwarno
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Large Scale ◽  
Logistic Regression Model ◽  
Banking Sector ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Access To Credit ◽  
The Poor ◽  
Micro Enterprises

Abstract: The number of micro-entrepreneurs and the dominant number of micro enterprises compared to medium and large-scale enterprises in Indonesia are not balanced by the provision of access to credit and venture capital for micro businesses. This resulted in a micro-sector sector identical to the poor being vulnerable to exploitation by moneylenders who exploit the difficulties of micro entrepreneurs accessing credit from the banking sector. This study examines the factors that determine the accessibility of credit by micro entrepreneur in Bojonegoro regency. A total sum of 270 micro entrepreneurs who have applied for banking loan were sampled from the study area. With an binary logistic regression model the research resulting that education, skill on entrepreneur, and monthly net profits generated by the microenterprise are significant in determining the accessibility of microcredit. Keywords: micro entrepreneur, microcredit, credit accessibility Abstrak: Perkembangan jumlah pengusaha mikro serta dominannya jumlah usaha mikro dibandingkan dengan usaha menengah dan usaha besar di Indonesia, tidak diimbingi dengan penyediaan akses kredit dan modal usaha bagi para pelaku usaha mikro. Hal tersebut mengakibatkan sektor usaha mikro yang identik dengan masyarakat miskin rentan dieksploitasi oleh rentenir yang memanfaatkan sulitnya para pengusaha mikro mengakses kredit dari sektor perbankan. Penelitian ini menggunakan data primer yang di ambil langsung dari pengusaha mikro dengan teknik kuesioner. Analisis data dengan metode binary logistic regression mendapatkan hasil variabel yang berpengaruh signifikan terhadap akses kredit para pengusaha mikro adalah variabel usia pengusaha, laba bersih usaha tiap bulan, dan jumlah karyawan yang di pekerjakan. Kata kunci : usaha mikro, microcredit, akses kredit

Die Flexion der Indefinita jemand und niemand

2021 ◽  
Vol 49 (2) ◽  
pp. 209-243
Author(s):  
Linnéa Weitkamp
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Influencing Factors ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Corpus Study ◽  
Frequent Use ◽  
Current Variation ◽  
Reference Corpus

Abstract This article investigates the inflection of the German indefinite pronouns jemand and niemand in the accusative and dative. The pronouns are used both with inflectional suffix (jemanden/jemandem, niemanden/niemandem) and without (jemand, niemand) and are thus an example of current variation in contemporary German. The grammars take an unusually liberal stance and describe both forms as correct, partially even with preference to the uninflected form. A corpus study which examines conceptually written data of the DeReKo (German reference corpus) and conceptually oral data of the DECOW16B (German web corpus), shows that over 90 % of occurrences are inflected. But almost 10 % of uninflected forms show that these formations are no arbitrary errors either. To find out what influences the presence or absence of the inflectional ending, a binary logistic regression model was calculated. The following factors proved to be significant influencing factors for inflection: the degree of formality (DeReKo vs. DECOW16B), the lexeme (jemand vs. niemand), the case (acc vs. dat), government by preposition vs. government by verb and the following nominalized adjective (jemand anderen). With regard to the different inflectional suffixes, the frequent use of -en in the dative stood out in particular. Although this form is classified as erroneous in all grammars, almost 30 % of the dative occurrences in informal DECOW16B data are formed in this way.

Sign in / Sign up

Export Citation Format

Share Document