MODEL REGRESI LINEAR PARTIAL LEAST SQUARE TERGENERALISASI PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION
The core of the linear regression model is to find the values of the coefficient estimator explanatory variables on the dependent variable so as to provide the error value as small as possible. There are many methods that have been studied including the popular classical method called OLS as well as...
| Main Authors: | , |
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2012
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| Subjects: |
| _version_ | 1826045957176819712 |
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| author | , ANI APRIANI , Prof. Dr. Sri Haryatmi, M.Sc |
| author_facet | , ANI APRIANI , Prof. Dr. Sri Haryatmi, M.Sc |
| author_sort | , ANI APRIANI |
| collection | UGM |
| description | The core of the linear regression model is to find the values of the
coefficient estimator explanatory variables on the dependent variable so as to
provide the error value as small as possible. There are many methods that have
been studied including the popular classical method called OLS as well as
iterative methods such as WLS, robust can be used to determine estimator in the
regression model. However, when there is multicollinearity among the
explanatory variables, using these methods, the regression coefficient becomes
more unstable. Therefore, in this paper the stepwise regression method called
Partial least square is proposed. This method is a series of simple and multiple
regressions by creating new explanatory variables that is a linear combination of
the original explanatory variables. By taking the statistical test related to linear
regression, it is possible to choose independent significant variables used in the
Partial Least Square regression. The multicollinearity case study on the logistic
regression shows that the partial least square provides better estimation. |
| first_indexed | 2024-03-13T22:45:37Z |
| format | Thesis |
| id | oai:generic.eprints.org:118164 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T22:45:37Z |
| publishDate | 2012 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1181642016-03-04T08:45:19Z https://repository.ugm.ac.id/118164/ MODEL REGRESI LINEAR PARTIAL LEAST SQUARE TERGENERALISASI PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION , ANI APRIANI , Prof. Dr. Sri Haryatmi, M.Sc ETD The core of the linear regression model is to find the values of the coefficient estimator explanatory variables on the dependent variable so as to provide the error value as small as possible. There are many methods that have been studied including the popular classical method called OLS as well as iterative methods such as WLS, robust can be used to determine estimator in the regression model. However, when there is multicollinearity among the explanatory variables, using these methods, the regression coefficient becomes more unstable. Therefore, in this paper the stepwise regression method called Partial least square is proposed. This method is a series of simple and multiple regressions by creating new explanatory variables that is a linear combination of the original explanatory variables. By taking the statistical test related to linear regression, it is possible to choose independent significant variables used in the Partial Least Square regression. The multicollinearity case study on the logistic regression shows that the partial least square provides better estimation. [Yogyakarta] : Universitas Gadjah Mada 2012 Thesis NonPeerReviewed , ANI APRIANI and , Prof. Dr. Sri Haryatmi, M.Sc (2012) MODEL REGRESI LINEAR PARTIAL LEAST SQUARE TERGENERALISASI PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=57808 |
| spellingShingle | ETD , ANI APRIANI , Prof. Dr. Sri Haryatmi, M.Sc MODEL REGRESI LINEAR PARTIAL LEAST SQUARE TERGENERALISASI PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION |
| title | MODEL REGRESI LINEAR PARTIAL LEAST SQUARE
TERGENERALISASI
PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION |
| title_full | MODEL REGRESI LINEAR PARTIAL LEAST SQUARE
TERGENERALISASI
PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION |
| title_fullStr | MODEL REGRESI LINEAR PARTIAL LEAST SQUARE
TERGENERALISASI
PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION |
| title_full_unstemmed | MODEL REGRESI LINEAR PARTIAL LEAST SQUARE
TERGENERALISASI
PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION |
| title_short | MODEL REGRESI LINEAR PARTIAL LEAST SQUARE
TERGENERALISASI
PARTIAL LEAST SQUARE GENERALISED LINEAR REGRESSION |
| title_sort | model regresi linear partial least square tergeneralisasi partial least square generalised linear regression |
| topic | ETD |
| work_keys_str_mv | AT aniapriani modelregresilinearpartialleastsquaretergeneralisasipartialleastsquaregeneralisedlinearregression AT profdrsriharyatmimsc modelregresilinearpartialleastsquaretergeneralisasipartialleastsquaregeneralisedlinearregression |