Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Minimum distance estimation in linear models with long range dependent errors.
AU - Mukherjee, Kanchan
PY - 1994/12/7
Y1 - 1994/12/7
N2 - This paper discusses the asymptotic representations of a class of L2-distance estimators based on weighted empirical processes in a multiple linear regression model when the errors are a function of stationary Gaussian random variables that are long-range dependent. Unlike the independent errors case, the limiting distributions of the suitably normalized estimators are not always normal. The limiting distributions depend heavily on the Hermite rank of a certain class of random variables. Some ‘goodness of fit’ tests for specified error distribution are also considered.
AB - This paper discusses the asymptotic representations of a class of L2-distance estimators based on weighted empirical processes in a multiple linear regression model when the errors are a function of stationary Gaussian random variables that are long-range dependent. Unlike the independent errors case, the limiting distributions of the suitably normalized estimators are not always normal. The limiting distributions depend heavily on the Hermite rank of a certain class of random variables. Some ‘goodness of fit’ tests for specified error distribution are also considered.
KW - Asymptotic uniform quadraticity
KW - Long-range dependence
KW - Hermite ranks and polynominals
U2 - 10.1016/0167-7152(94)00029-8
DO - 10.1016/0167-7152(94)00029-8
M3 - Journal article
VL - 21
SP - 347
EP - 355
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
SN - 0167-7152
IS - 5
ER -