Estimation of Covariance Matrix on Bi-Response Longitudinal Data Analysis with Penalized Spline Regression

Islamiyati, Anna; Fatmawati, Fatmawati; Chamidah, Nur

doi:10.1088/1742-6596/979/1/012093

Cited by 16 publications

(11 citation statements)

References 12 publications

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“…Hubungan antara jumlah kejadian kejahatan terhadap kesusilaan dan jumlah kejadian kejahatan terhadap fisik di Indonesia tahun 2020 dengan faktor-faktor yang memengaruhinya dapat dianalisis menggunakan metode analisis regresi birespon karena menggunakan dua variabel respon dan pendekatan nonparametrik digunakan saat fungsi data yang diperoleh tidak menunjukkan pola hubungan yang mudah digambarkan dengan fungsi tertentu. Salah satu pendekatan dalam regresi nonparametrik adalah estimator penalized spline yang memperhitungkan titik knot dan parameter penghalus secara bersamaan sehingga menghasilkan ketepatan dan kehalusan bentuk kurva secara simultan (Islamiyati, Fatmawati dan Chamidah, [7]).…”

Section: Pendahuluanunclassified

Estimasi Parameter Model Regresi Nonparametrik Birespon berdasarkan Penalized Spline Pada Data Tindak Kriminal di Indonesia (Studi Kasus Jumlah Kejadian Kejahatan terhadap Kesusilaan dan Jumlah Kejadian Kejahatan terhadap Fisik di Indonesia Tahun 2020)

Anggraeni

Gusriani

Parmikanti

2022

jmi

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To achieve the creation of a safe and peaceful social life, crime is one of the things that is very concerned. In 2020, in Indonesia there were 6.872 crimes against decency and 36.672 crimes against the physical. One of the efforts that can be done to reduce the number of incidents of crimes against decency and the number of incidents of physical crimes in Indonesia is to model it on the factors that influence it so that predictions can be obtained. In this study, an estimation of the parameters of the nonparametric biresponse regression model was carried out based on the penalized spline estimator using the Weighted Least Square (WLS) method approach to predict the number of crimes against decency and the number of incidents of physical crime in Indonesia in 2020 with the predictor variable population density (X 1 ), the ratio of sex gender (X 2 ), the percentage of poor people (X 3 ) and the average net wage of workers/employees/employees (X 4 ). The penalized spline estimator is used to calculate knot points and smoothing parameters simultaneously so as to produce accuracy and smoothness of the curve shape simultaneously. The best model depends on determining the knot point and optimal smoothing parameters, namely the minimum Generalized Cross Validation (GCV) value. The best model is obtained when the number of knots for X 1 is one, X 2 is three, X 3 is three, and X 4 is one and λ = 0, 000000171 with a GCV of 568.359 and coefficient of determination of 0.652.Keywords: the number of incidents of crimes against decency, the number of incidents of crimes against physical, biresponse nonparametric regression, penalized spline, WLS, GCV.

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Section: Pendahuluanunclassified

Estimasi Parameter Model Regresi Nonparametrik Birespon berdasarkan Penalized Spline Pada Data Tindak Kriminal di Indonesia (Studi Kasus Jumlah Kejadian Kejahatan terhadap Kesusilaan dan Jumlah Kejadian Kejahatan terhadap Fisik di Indonesia Tahun 2020)

Anggraeni

Gusriani

Parmikanti

2022

jmi

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“…Regresi merupakan analisis statistika yang digunakan untuk menyelidiki pola hubungan dan pengaruh beberapa variabel prediktor terhadap variabel respon [1]. Suatu model regresi dikatakan baik apabila memenuhi beberapa asumsi klasik, seperti asumsi normalitas dan homokedastisitas [2].…”

Section: Pendahuluanunclassified

Estimasi Model Regresi Kuantil Spline Kuadratik pada Data Trombosit dan Hematokrit Pasien DBD

et al. 2020

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Nonparametric quantile regression is used to estimate the regression function when assumptions about the shape of the regression curve are unknown. It is only assumed to be subtle by involving quantile values. One estimator in nonparametric regression is spline. The segmented properties of the spline provide more flexibility than ordinary polynomials. Therefore, the nature of the spline makes it possible to adapt more effectively to the local characteristics of a function or data. This study proposes to get the results of the estimation platelet count model to the hematocrit value of DHF. The optimal model obtained from the estimation of quadratic spline quantile regression is at quantile 0.5 with one knot and the GCV value is 41.5. The results of the estimation show that there is a decrease in platelet counts as the percentage of hematocrit increase.

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“…Estimator spline yang diperoleh dengan menggunakan metode least square disebut least square Spline. Peneliti yang menggunakan estimator spline dalam regresi nonparametrik antara lain Lestari et al [4], Islamiyati, et al [5] and Ayidin and Yilmaz [6].…”

Section: Pendahuluanunclassified

Analisis Pengaruh Angka Kematian Bayi Terhadap Angka Harapan Hidup Di Provinsi Jawa Timur Berdasarkan Estimator Least Square Spine

Novia

Tegarina

et al. 2019

Contemp. Math. App

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Life expectancy can be used to evaluate the government's performance for improving the welfare of the population in the health sector. Life expectancy is closely related to infant mortality rate. Theoretically, decreasing of infant mortality rate will cause increasing of life expectancy. A statistical method that can be used to model life expectancy is nonparametric regression model based on least square spline estimator. This method provides high flexibility to accommodate pattern of data by using smoothing technique. The best estimated model is order one spline model with one knot based on minimum generalized cross validation (GCV) value of 0.607. Each increasing of one infant mortality rate unit will cause decreasing of life expectancy of 0.2314 for infant mortality rate less than 27, and of 0.0666 for infant mortality rate more than and equals to 27. In addition, based on mean square error (MSE) of 0.492 and R2value of 76.59% for nonparametric model approach compared with MSE of 0.634 and R2 value of 71.8% for parametric model approach, we conclude that the use of nonparametric model approach based on least square spline estimator is better than that of parametric model approach.

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Estimation of Covariance Matrix on Bi-Response Longitudinal Data Analysis with Penalized Spline Regression

Cited by 16 publications

References 12 publications

Estimasi Parameter Model Regresi Nonparametrik Birespon berdasarkan Penalized Spline Pada Data Tindak Kriminal di Indonesia (Studi Kasus Jumlah Kejadian Kejahatan terhadap Kesusilaan dan Jumlah Kejadian Kejahatan terhadap Fisik di Indonesia Tahun 2020)

Estimasi Parameter Model Regresi Nonparametrik Birespon berdasarkan Penalized Spline Pada Data Tindak Kriminal di Indonesia (Studi Kasus Jumlah Kejadian Kejahatan terhadap Kesusilaan dan Jumlah Kejadian Kejahatan terhadap Fisik di Indonesia Tahun 2020)

Estimasi Model Regresi Kuantil Spline Kuadratik pada Data Trombosit dan Hematokrit Pasien DBD

Analisis Pengaruh Angka Kematian Bayi Terhadap Angka Harapan Hidup Di Provinsi Jawa Timur Berdasarkan Estimator Least Square Spine

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