A family of Root Mean Square Error of Approximation (RMSEA) statistics is proposed for assessing the goodness of approximation in discrete multivariate analysis with applications to item response theory (IRT) models. The family includes RMSEAs to assess the approximation up to any level of association of the discrete variables. Two members of this family are RMSEA2, which uses up to bivariate m...

Abstract. The root-mean-squared error (RMSE) and mean absolute (MAE) are widely used metrics for evaluating models. Yet, there remains enduring confusion over their use, such that a standard practice is to present both, leaving it the reader decide which more relevant. In recent reprise 200-year debate Willmott Matsuura (2005) Chai Draxler (2014) give arguments favoring one metric or other. How...

response surface methodology (rsm) is a statistical method useful in the modeling and analysis of problems in which the response variable receives the influence of several independent variables, in order to determine which are the conditions under which should operate these variables to optimize a corrugated box production process. the purpose of this research is to create response surface mode...

Consider the class of Ensemble Square Root filtering algorithms for numerical approximation posterior distribution nonlinear Markovian signals partially observed with linear observations corrupted independent measurement noise. We analyze asymptotic behavior these in large ensemble limit both discrete and continuous time. identify limiting mean-field processes on level members, prove correspond...