ESTIMASI PARAMETER DAN UJI HIPOTESIS PADA MODEL LINEAR MULTIVARIAT DENGAN METODE LDL
Keywords: estimation of parameter, likelihood displacement statistic-lagrange, multivariate linear models, outlier detection
Abstract
Outliers are observations (data) that lies in an abnormal distance from other observations. Outliers can be distinguished into outliers of univariate or multivariate observation and outliers of univariate or multivariate linear models. Multivariate linear model is a linear model with more than one dependent (response) variables. This research studied parameter estimation and hypothesis test for multivariate linear model using Likelihood Displacement Statistic-Lagrange Method called as LDL method for detecting outlier observations in multivariate linear models with the LDLAm statistical test.
Downloads
Download data is not yet available.
References
Barnett, V. & Lewis, T. (1994). Outliers in statistical data. ( ed). Great Britain: John Wiley.
Christensen, R. (1991). Linear model for multivariate, time series, and spatial data. New York: Springer-Verlag.
Cook, R.D. (1977). Detection of influential observation in linear regression. Technometrics, Februari 2000, 42, no. (1), 65-68.
Diaz-Garcia, J.A., Gonzalez-Farias, G. & Alvarado-Castro, V. (2007). Exact distributions for sensitivity analysis in linear regression. Applied Mathematical Sciences, 22;1083-1100.
Filzmoser, P. (2005). Identification of multivariate outliers: A performance study. Austrian Journal of Statistics. 2;127-138.
Hawkins, D.M. (1980). Identifications of outliers. New York: Chapman and Hall.
Makkulau, Linuwih, S., Purhadi, & Mashuri, M. (2007a). Outlier detection for the value of Y variable (residual outlier) in multivariate regression models. Proceeding International Conference and Workshop on Basic and Applied Science, Universitas Airlangga, Agustus 2007, Surabaya.
Makkulau, Linuwih, S., Purhadi, & Mashuri, M. (2007b). Pendeteksian outlier pada model linear multivariat dengan pergeseran rata-rata. Prosiding Seminar Nasional Statis-tika VIII, Jurusan Statistika FMIPA ITS, November 2007, Surabaya.
Makkulau, Linuwih, S., Purhadi, & Mashuri, M. (2008). Prosedur pendeteksian outlier pada model linear multivariat dengan metode likelihood displacement statistic. Prosiding Seminar Nasional Matematika IV, Jurusan Matematika FMIPA ITS, Desember 2008, Surabaya.
Makkulau, Linuwih, S., Purhadi, & Mashuri, M. (2009). Pendeteksian outlier model linear multivariat pada produksi gula dan tetes tebu. Prosiding Seminar Nasional Matematika, Jurusan Matematika FMIPA Universitas Jember, Februari 2009, Jember.
Pea, D. & Guttman, I. (1993). Comparing probabilistic methods for outlier detection in linear models. Biometrika, Technometrics, August 2001. 3;603-610.
Pea, D. & Prieto, F.J. (2001). Multivariate outlier detection and robust covariance matrix estimation. American Statistical Association and the American Society for Quality, Technometrics. 43, no (3).
Rencher, A.C. & Schaalje, G.B. (2008). Linear models in Statistics, (2nd ed). John Wiley & Sons: New York.
Rousseeuw, P.J. (1984). Least median of squares regression. Journal of the American Statistical Association. 79, 871-880.
Rousseeuw, P.J. & Hubert, M. (1997). Recent developments in PROGRESS, dalam L1-Statistical procedure and related topics, edited by Y. Dodge, Institute of Mathematical Statistics Lecture Notes and Monograph Series, Hayward, California, Vol. 31, 201-214.
Srivastava, M.S. & von Rosen, D. (1998). Outliers in multivariate regression models, Journal of Multivariate Analysis. 65, 195-208.
Xu, J., Abraham, B., & Steiner, S.H. (2005). Outlier detection methods in multivariate regression models. Diambil tanggal 4 April 2007, dari http://www.bisrg.uwaterloo.ca/archive/RR-06-07.pdf.
Christensen, R. (1991). Linear model for multivariate, time series, and spatial data. New York: Springer-Verlag.
Cook, R.D. (1977). Detection of influential observation in linear regression. Technometrics, Februari 2000, 42, no. (1), 65-68.
Diaz-Garcia, J.A., Gonzalez-Farias, G. & Alvarado-Castro, V. (2007). Exact distributions for sensitivity analysis in linear regression. Applied Mathematical Sciences, 22;1083-1100.
Filzmoser, P. (2005). Identification of multivariate outliers: A performance study. Austrian Journal of Statistics. 2;127-138.
Hawkins, D.M. (1980). Identifications of outliers. New York: Chapman and Hall.
Makkulau, Linuwih, S., Purhadi, & Mashuri, M. (2007a). Outlier detection for the value of Y variable (residual outlier) in multivariate regression models. Proceeding International Conference and Workshop on Basic and Applied Science, Universitas Airlangga, Agustus 2007, Surabaya.
Makkulau, Linuwih, S., Purhadi, & Mashuri, M. (2007b). Pendeteksian outlier pada model linear multivariat dengan pergeseran rata-rata. Prosiding Seminar Nasional Statis-tika VIII, Jurusan Statistika FMIPA ITS, November 2007, Surabaya.
Makkulau, Linuwih, S., Purhadi, & Mashuri, M. (2008). Prosedur pendeteksian outlier pada model linear multivariat dengan metode likelihood displacement statistic. Prosiding Seminar Nasional Matematika IV, Jurusan Matematika FMIPA ITS, Desember 2008, Surabaya.
Makkulau, Linuwih, S., Purhadi, & Mashuri, M. (2009). Pendeteksian outlier model linear multivariat pada produksi gula dan tetes tebu. Prosiding Seminar Nasional Matematika, Jurusan Matematika FMIPA Universitas Jember, Februari 2009, Jember.
Pea, D. & Guttman, I. (1993). Comparing probabilistic methods for outlier detection in linear models. Biometrika, Technometrics, August 2001. 3;603-610.
Pea, D. & Prieto, F.J. (2001). Multivariate outlier detection and robust covariance matrix estimation. American Statistical Association and the American Society for Quality, Technometrics. 43, no (3).
Rencher, A.C. & Schaalje, G.B. (2008). Linear models in Statistics, (2nd ed). John Wiley & Sons: New York.
Rousseeuw, P.J. (1984). Least median of squares regression. Journal of the American Statistical Association. 79, 871-880.
Rousseeuw, P.J. & Hubert, M. (1997). Recent developments in PROGRESS, dalam L1-Statistical procedure and related topics, edited by Y. Dodge, Institute of Mathematical Statistics Lecture Notes and Monograph Series, Hayward, California, Vol. 31, 201-214.
Srivastava, M.S. & von Rosen, D. (1998). Outliers in multivariate regression models, Journal of Multivariate Analysis. 65, 195-208.
Xu, J., Abraham, B., & Steiner, S.H. (2005). Outlier detection methods in multivariate regression models. Diambil tanggal 4 April 2007, dari http://www.bisrg.uwaterloo.ca/archive/RR-06-07.pdf.
Published
Aug 15, 2010
How to Cite
Makkulau, M., Linuwih, S., Purhadi, P., Mashuri, M., & Pane, R. (2010). ESTIMASI PARAMETER DAN UJI HIPOTESIS PADA MODEL LINEAR MULTIVARIAT DENGAN METODE LDL. Jurnal Matematika Sains Dan Teknologi, 11(1), 1–9. Retrieved from http://jurnal.ut.ac.id/index.php/jmst/article/view/548
Download Citation
Issue
Section
Articles