A Selective Overview of Semiparametric Mixture of Regression Models

2018 ◽  
pp. 41-65
Author(s):  
Sijia Xiang ◽  
Weixin Yao
Keyword(s):  
Regression Models ◽  
Semiparametric Mixture

Regression Models of Foreign Policy Beliefs

1968 ◽  
Author(s):  
David A. Summers ◽  
Thomas R. Stewart
Keyword(s):  
Foreign Policy ◽  
Regression Models ◽  
Policy Beliefs

A Multivariate Approach to Lexical Diversity in Constrained Language

2020 ◽  
Vol 21 (2) ◽  
pp. 169-194
Author(s):  
Marta Kajzer-Wietrzny ◽  
Ilmari Ivaska
Keyword(s):  
Second Language Acquisition ◽  
Regression Models ◽  
Translation Studies ◽  
Methodological Framework ◽  
Multivariate Approach ◽  
Mediated Communication ◽  
Vocabulary Size ◽  
Lexical Diversity ◽  
Linear Mixed Effects ◽  
Word Repetition

Empirical Translation Studies have recently extended the scope of research to other forms of constrained and mediated communication, including bilingual communication, editing, and intralingual translation. Despite the diversity of factors accounted for so far, this new strand of research is yet to take the leap into intermodal comparisons. In this paper we look at Lexical Diversity (LD), which under different guises, has been studied both within Translation Studies (TS) and Second Language Acquisition (SLA). LD refers to the rate of word repetition, and vocabulary size and depth, and previous research indicates that translated and non-native language tends to be less lexically diverse. There is, however, no study that would investigate both varieties within a unified methodological framework. The study reported here looks at LD in spoken and written modes of constrained and non-constrained language. In a two-step analysis involving Exploratory Factor Analysis and linear mixed-effects regression models we find interpretations to be least lexically diverse and written non-constrained texts to be most diverse. Speeches delivered impromptu are less diverse than those read out loud and the non-constrained texts are more sensitive to such delivery-related differences than the constrained ones.

An Optimal Weight Predictor for Hierarchical Regression Models

1986 ◽  
Vol 13 (20) ◽  
pp. 13-21
Author(s):  
Nobuyuki Kawai
Keyword(s):  
Regression Models ◽  
Hierarchical Regression ◽  
Optimal Weight
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