نتایج جستجو برای: test and multivariate regression
تعداد نتایج: 16928751 فیلتر نتایج به سال:
monumental changes occurring on a daily basis have altered the world into a global village of expanding technology and shrinking geography in which preparing language learners for intercultural communication seems to be a sine qua non for modern language education. employing a cross-sectional design in its first phase, this study investigated the intercultural sensitivity and language proficien...
this study sought to examine the effect of cooperative game on iranian students achievements in english alphabet learning. cooperative games are games, in which players or teams work together towards a common goal without defeating someone. the methodology used in this study was experimental. the population of the study was 60 female students from the grade one in secondary school in tabriz, ir...
thermal barrier coatings (tbcs) are used to provide thermal insulation to the hot section components of gas turbines in order to enhance the operating temperature and turbine efficiency. hot corrosion and thermal shocks are the main destructive factors in tbcs which comes as a result of oxygen and molten salt diffusion into the coating. in this thesis atmospheric plasma spraying was used to dep...
We consider in this paper the multivariate regression problem, when the target regression matrix A is close to a low rank matrix. Our primary interest is in on the practical case where the variance of the noise is unknown. Our main contribution is to propose in this setting a criterion to select among a family of low rank estimators and prove a non-asymptotic oracle inequality for the resulting...
A “multivariate interaction” in a regression model is a product of two independent variates (linear functions of the regressors) that is an additive component of the regression function E(Y |X). In many cases a substantial portion of the overall pairwise interaction structure in a regression function can be captured by a single multivariate interaction. Due to its parsimonious form, a multivari...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional multivariate regression models. Compared to existing methods, CMR calibrates the regularization for each regression task with respect to its noise level so that it is simultaneously tuning insensitive and achieves an improved finite-sample performance. Computationally, we develop an efficient smo...
In many high dimensional problems, the dependence structure among the variables can be quite complex. An appropriate use of the regularization techniques coupled with other classical statistical methods can often improve estimation and prediction accuracy and facilitate model interpretation, by seeking a parsimonious model representation that involves only the subset of revelent variables. We p...
the primary goal of the current project was to examine the effect of three different treatments, namely, models with explicit instruction, models with implicit instruction, and models alone on differences between the three groups of subjects in the use of the elements of argument structures in terms of toulmins (2003) model (i.e., claim, data, counterargument claim, counterargument data, rebutt...
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