Uniqueness of the least-distances estimator in regression models with multivariate response

1995 ◽  
Vol 23 (4) ◽  
pp. 421-424 ◽  
Author(s):  
Gilles R. Ducharme
2017 ◽  
Vol 5 (1) ◽  
pp. 268-294 ◽  
Author(s):  
Giampiero Marra ◽  
Rosalba Radice

Abstract We discuss some of the features of the R add-on package GJRM which implements a flexible joint modeling framework for fitting a number of multivariate response regression models under various sampling schemes. In particular,we focus on the case inwhich the user wishes to fit bivariate binary regression models in the presence of several forms of selection bias. The framework allows for Gaussian and non-Gaussian dependencies through the use of copulae, and for the association and mean parameters to depend on flexible functions of covariates. We describe some of the methodological details underpinning the bivariate binary models implemented in the package and illustrate them by fitting interpretable models of different complexity on three data-sets.


2020 ◽  
Vol 21 (2) ◽  
pp. 169-194
Author(s):  
Marta Kajzer-Wietrzny ◽  
Ilmari Ivaska

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.


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