Corrigendum to “Asymptotic results in segmented multiple regression” [J. Multivariate Anal. 99 (2008) 2016–2038]

Erratum to "Construction of asymmetric multivariate copulas" [J. Multivariate Anal. 99(2008) 2234-2250]

Assume that C1, . . . , Ck : [0, 1]d → [0, 1] are copulas. Let gji : [0, 1] → [0, 1] for j = 1, . . . , k, i = 1, . . . , d be functions with the property that each of them is strictly increasing or is identically equal to 1. Suppose that ∏k j=1 gji(v) = v for v ∈ [0, 1], i = 1, . . . , d, and limv→0+0 gij(v) = gji(0) for j = 1, . . . , k, i = 1, . . . , d. Here we consider the two-dimensional ...

On Segmented Multivariate Regression

This paper concerns segmented multivariate regression models, models which have different linear forms in different subdomains of the domain of an independent variable. Without knowing that number and their boundaries, we first estimate the number of these subdomains using a modified Schwarz criterion. The estimated number of regions proves to be weakly consistent under fairly general condition...

Corrigendum to "Ridge regression estimation approach to measurement error model" [J. Multivariate Analysis 123 (2014) 68-84]

Some Modifications to Calculate Regression Coefficients in Multiple Linear Regression

In a multiple linear regression model, there are instances where one has to update the regression parameters. In such models as new data become available, by adding one row to the design matrix, the least-squares estimates for the parameters must be updated to reflect the impact of the new data. We will modify two existing methods of calculating regression coefficients in multiple linear regres...

Asymptotic equivalence for nonparametric regression with multivariate and random design

We show that nonparametric regression is asymptotically equivalent in Le Cam’s sense with a sequence of Gaussian white noise experiments as the number of observations tends to infinity. We propose a general constructive framework based on approximation spaces, which permits to achieve asymptotic equivalence even in the cases of multivariate and random design.