摘要:

A brief review and bibliography of least absolute values (LAV) estimation is given. This paper serves to introduce the other articles in this special issue on the computational aspects of LAV estimation.

ISSN:0361-0918    

DOI:10.1080/03610917708812047

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

摘要:

The Barrodale and Roberts algorithm for least absolute value (LAV) regression and the algorithm proposed by Bartels and Conn both have the advantage that they are often able to skip across points at which the conventional simplex-method algorithms for LAV regression would be required to carry out an (expensive) pivot operation.

ISSN:0361-0918    

DOI:10.1080/03610917708812048

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

摘要:

We propose an algorithm to estimate the unknown constants in a multiple linear regression model under the minimum sum of weighted absolute errors (MSWAE). The proposed algorithm, a generalization of an earlier algorithm, is compared to a bounded variable algorithm. Some somputational experience is reported.

ISSN:0361-0918    

DOI:10.1080/03610917708812049

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

摘要:

We present a concise summary of recent progress in developing algorithms for restricted least absolute value (LAV) estimation (i. e. ℓ1approximation subject to linear constraints). The emphasis is on our own new algorithm, and we provide some numerical results obtained with it.

ISSN:0361-0918    

DOI:10.1080/03610917708812050

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

摘要:

The importance of the two-way classification model is well known, but the standard method of analysis is least squares. Often, the data of the model calls for a more robust estimation technique. This paper demonstrates the equivalence between the problem of obtaining least absolute value estimates for the two-way classification model and a capacitated transportation problem. A special purpose primal algorithm is developed to provide the least absolute value estimates. A computational comparison is made between an implementation of this specialized algorithm and a standard capacitated transportation code.

ISSN:0361-0918    

DOI:10.1080/03610917708812051

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

摘要:

Dummy (0, 1) variables are frequently used in statistical modeling to represent the effect of certain extraneous factors. This paper presents a special purpose linear programming algorithm for obtaining least-absolute-value estimators in a linear model with dummy variables. The algorithm employs a compact basis inverse procedure and incorporates the advanced basis exchange techniques available in specialized algorithms for the general linear least-absolute-value problem. Computational results with a computer code version of the algorithm are given.

ISSN:0361-0918    

DOI:10.1080/03610917708812052

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

摘要:

This is the first of a projected series of papers dealing with computational experimentation in mathematical programming. This paper provides early results of a test case using four discrete linear L1approximation codes. Variables influencing code behavior are identified and measures of performance are specified. More importantly, an experimental design is developed for assessing code performance and is illustrated using the variable “problem size”.

ISSN:0361-0918    

DOI:10.1080/03610917708812053

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

摘要:

Two techniques for detecting inaccuracies in least absolute values (LAV) regression computations are presented and discussed. Examples of the use of the methods are given. The techniques are shown to apply to the more general case of M-estimation.

ISSN:0361-0918    

DOI:10.1080/03610917708812054

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

摘要:

For multivariate regression with a symmetric disturbance distribution, the error in the least absolute residuals estimator is approximately multivariate normally distributed with mean zero and variance matrix λ2(X′X)−1, where X is the matrix of K explanatory variables and T observations, and λ2/T is the variance of the median of a sample of size T from the disturbance distribution. The approximate sampling theory is validated by extensive Monte Carlo studies, and some directions of possible refinement emerge.

ISSN:0361-0918    

DOI:10.1080/03610917708812055

出版商:Marcel Dekker, Inc.    

年代:1977

数据来源: Taylor

ISSN:0361-0918    

DOI:10.1080/03610917708812046

出版商:Marcel Dekker, Inc    

年代:1977

数据来源: Taylor