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Journal articles on the topic 'Generalized cross-validation (GCV)'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Maharani, M., and D. R. S. Saputro. "Generalized Cross Validation (GCV) in Smoothing Spline Nonparametric Regression Models." Journal of Physics: Conference Series 1808, no. 1 (2021): 012053. http://dx.doi.org/10.1088/1742-6596/1808/1/012053.

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Lamusu, Febriolah, Tedy Machmud, and Resmawan Resmawan. "Estimator Nadaraya-Watson dengan Pendekatan Cross Validation dan Generalized Cross Validation untuk Mengestimasi Produksi Jagung." Indonesian Journal of Applied Statistics 3, no. 2 (2021): 85. http://dx.doi.org/10.13057/ijas.v3i2.42125.

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<p>Nadaraya-Watson Estimator with kernel approach depends on two-parameter, those are kernel function and bandwidth choice. However, between the two of them, bandwidth choice gave a huge impact on the result of the estimation. By minimizing the value of Mean Square Error (MSE), Cross-Validation (CV) and Generalized Cross-Validation (GCV) gave the optimal bandwidth value. In this research, corn production was considered as the dependent variable, while the planted area, harvested area, and the fertilizer as the independent variable. The result of this research showed that Nadaraya-Watson

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Fang, Yuan, Jun Wang, Xiaohong Meng, and Hanhan Tang. "Improved Generalized Cross-Validation and Unbiased Predictive Risk Estimator Methods Using the RGSVD: Application to Inversion of Potential Field Data." Applied Sciences 11, no. 14 (2021): 6326. http://dx.doi.org/10.3390/app11146326.

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The inversion of potential field data has widely utilized the generalized cross-validation (GCV) and the unbiased predictive risk estimator (UPRE) methods to determine the regularization parameter. However, these two methods are time-consuming and it is difficult for them to determine the optimal linear search range including the optimal regularization. To solve these problems, this article improves the GCV and UPRE methods using the RGSVD (randomized generalized singular value decomposition) algorithm. The improved methods first use the randomized algorithm to compute an approximate generaliz

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Tripena Br. Sb., Agustini. "PEMILIHAN PARAMETER PENGHALUS DALAM REGRESI SPLINE LINIER." Jurnal Ilmiah Matematika dan Pendidikan Matematika 3, no. 1 (2011): 9. http://dx.doi.org/10.20884/1.jmp.2011.3.1.2969.

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This paper discusses aselection of smoothing parameters for the linier spline regression estimation on the data of electrical voltage differences in the wastewater. The selection methods are based on the mean square errorr (MSE) and generalized cross validation (GCV). The results show that in selection of smooting paranceus the mean square error (MSE) method gives smaller value , than that of the generalized cross validatio (GCV) method. It means that for our data case the errorr mean square (MSE) is the best selection method of smoothing parameter for the linear spline regression estimation.

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Pratiwi, Luh Putu Safitri. "PERBANDINGAN METODE CROSS VALIDATION DAN GENERALIZED CROSS VALIDATION DALAM REGRESI NONPARAMETRIK BIRESPON SPLINE." Jurnal Varian 1, no. 1 (2017): 43. http://dx.doi.org/10.30812/varian.v1i1.49.

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AbstrakAnalisis regresi merupakan salah satu metode yang sangat populer dalam statistika untuk menjelaskan hubungan sebab akibat antara satu/beberapa variabel prediktor terhadap satu variabel respon. Pada umumnya, pemodelan yang dapat dilakukan dengan menggunakan analisis regresi. Kurva regresi dapat diduga dengan pendekatan regresi parametrik dan pendekatan regresi nonparametrik. Namun, tidak semua data yang diperoleh mengikuti pola tertentu sehingga jenis data ini menggunakan pendekatan regresi nonparametrik. Pendekatan regresi nonparametrik tidak terkait dengan asumsi bentuk kurva regresi s

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Sanusi, Wahidah, Rahmat Syam, and Rabiatul Adawiyah. "Model Regresi Nonparametrik dengan Pendekatan Spline (Studi Kasus: Berat Badan Lahir Rendah di Rumah Sakit Ibu dan Anak Siti Fatimah Makassar)." Journal of Mathematics, Computations, and Statistics 2, no. 1 (2020): 70. http://dx.doi.org/10.35580/jmathcos.v2i1.12460.

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Pendekatan nonparametrik merupakan suatu pendekatan yang digunakan apabila bentuk hubungan antara variabel respon dan variabel prediktornya tidak diketahui atau tidak adanya informasi mengenai bentuk fungsi regresinya. Spline merupakan suatu teknik yang dilakukan untuk mengestimasi parameter dalam regresi nonparametrik. Penelitian ini bertujuan untuk mengetahui model hubungan antara berat badan lahir rendah dan faktor-faktor yang mempengaruhi berdasarkan model spline. Faktor-faktor tersebut adalah usia ibu, usia kehamilan, dan jarak kehamilan. Data tersebut diperoleh dari rumah sakit ibu dan a

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Rahasia, Zulaiha, Resmawan Resmawan, and Dewi Rahmawaty Isa. "Pemodelan Data Time Series dengan Pendekatan Regresi Nonparametrik B-Spline." AKSIOMA : Jurnal Matematika dan Pendidikan Matematika 11, no. 1 (2020): 9–16. http://dx.doi.org/10.26877/aks.v11i1.4903.

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Spline is one of the nonparametric approach, to adjust data so the final model has good flexibility. The purpose of this research is to model the time series data in the form of currency exchange rates by using the nonparametric B-spline approach. In B-spline modelling, determination of the order for the model, and the number and the placement of the knot are the criteria that must be considered. The best B-spline model obtained based on the selection of the optimal knot points with minimum Generalized Cross Validation (GCV) criteria. The modelling in this research use data on the exchange rat

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Wahyuningsih, Trionika Dian, Sri Sulistijowati Handajani, and Diari Indriati. "Penerapan Generalized Cross Validation dalam Model Regresi Smoothing Spline pada Produksi Ubi Jalar di Jawa Tengah." Indonesian Journal of Applied Statistics 1, no. 2 (2019): 117. http://dx.doi.org/10.13057/ijas.v1i2.26250.

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<p>Sweet Potato is a useful plant as a source carbohydrates, proteins, and is used as an animal feed and ingredient industry. Based on data from the Badan Pusat Statistik (BPS), the production fluctuations of the sweet potato in Central Java from year to year are caused by many factor. The production of sweet potato and the factors that affected it if they are described into a pattern of relationships then they do not have a specific pattern and do not follow a particular distribution, such as harvest area, the allocation of subsidized urea fertilizer, and the allocation of subsidized or

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O L, Maria Fatima. "Pemodelan Regresi Spline pada Studi Kasus Angka Kematian Bayi di Jawa Timur Tahun 2015." J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika 11, no. 2 (2018): 9–16. http://dx.doi.org/10.36456/jstat.vol11.no2.a2177.

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The question facing the East Java province in the field of health is maternal mortality (AKI) and infant mortality (AKB) which has decreased slowly. With regard to the target of the Millennium Development Goals (MDGs) in 2015 to AKB is the 23 deaths per 1.000 live births. AKB in East Java province, according to the Central Bureau of statistics (BPS) in 2015 i.e. amounting to 24 deaths per 1.000 live births. Based on the high degree of AKB in East Java the year 2015 then regression splines method applied to analyze AKB and the factors that affected it. Analysis of the results obtained that the

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Tsujitani, Masaaki, Yusuke Tanaka, and Masato Sakon. "Survival Data Analysis with Time-Dependent Covariates Using Generalized Additive Models." Computational and Mathematical Methods in Medicine 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/986176.

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We discuss a flexible method for modeling survival data using penalized smoothing splines when the values of covariates change for the duration of the study. The Cox proportional hazards model has been widely used for the analysis of treatment and prognostic effects with censored survival data. However, a number of theoretical problems with respect to the baseline survival function remain unsolved. We use the generalized additive models (GAMs) with B splines to estimate the survival function and select the optimum smoothing parameters based on a variant multifold cross-validation (CV) method.

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Adhi, Mochamad Aryono, Wahyudi Wahyudi, Wiwit Suryanto, and Muh Sarkowi. "GRAV3D Validation using Generalized Cross-Validation (GCV) Algorithm by Lower Bounds Approach for 3D Gravity Data Inversion." Scientific Journal of Informatics 5, no. 2 (2018): 271–77. http://dx.doi.org/10.15294/sji.v5i2.16736.

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The completion of gravitational data inversion results in a smooth recovered model. GRAV3D is one software that can be used to solve 3D inversion problems of gravity data. Nevertheless there are still fundamental problems related to how to ensure the validity of GRAV3D to be used in 3D inversion. One approach used is to use lower bounds as inversion parameters. In this study lower bounds are set from to . The results obtained show that the use of lower bounds decreases resulting in a larger data misfit which means that the more data that meets the tolerance calculation, the better recovered mo

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Kerkri, Abdelmounaim, Jelloul Allal, and Zoubir Zarrouk. "The L-Curve Criterion as a Model Selection Tool in PLS Regression." Journal of Probability and Statistics 2019 (October 30, 2019): 1–7. http://dx.doi.org/10.1155/2019/3129769.

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Partial least squares (PLS) regression is an alternative to the ordinary least squares (OLS) regression, used in the presence of multicollinearity. As with any other modelling method, PLS regression requires a reliable model selection tool. Cross validation (CV) is the most commonly used tool with many advantages in both preciseness and accuracy, but it also has some drawbacks; therefore, we will use L-curve criterion as an alternative, given that it takes into consideration the shrinking nature of PLS. A theoretical justification for the use of L-curve criterion is presented as well as an app

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Zin, Muhammad Athif Mat, Azmin Sham Rambely, Noratiqah Mohd Ariff, and Muhammad Shahimi Ariffin. "Smoothing and Differentiation of Kinematic Data Using Functional Data Analysis Approach: An Application of Automatic and Subjective Methods." Applied Sciences 10, no. 7 (2020): 2493. http://dx.doi.org/10.3390/app10072493.

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Smoothing is one of the fundamental procedures in functional data analysis (FDA). The smoothing parameter λ influences data smoothness and fitting, which is governed by selecting automatic methods, namely, cross-validation (CV) and generalized cross-validation (GCV) or subjective assessment. However, previous biomechanics research has only applied subjective assessment in choosing optimal λ without using any automatic methods beforehand. None of that research demonstrated how the subjective assessment was made. Thus, the goal of this research was to apply the FDA method to smoothing and differ

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SUKERNI, NI LUH, I. KOMANG GDE SUKARSA, and NI LUH PUTU SUCIPTAWATI. "PENDEKATAN REGRESI SPLINE UNTUK MEMODELKAN POLA PERTUMBUHAN BERAT BADAN BALITA." E-Jurnal Matematika 7, no. 3 (2018): 259. http://dx.doi.org/10.24843/mtk.2018.v07.i03.p212.

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The study is aimed to estimate the best spline regression model for toddler’s weight growth patterns. Spline is one of the nonparametric regression estimation method which has a high flexibility and is able to handle data that change in particular subintervals so thus resulting in model which fitted the data. This study uses data of toddler’s weight growth at Posyandu Mekar Sari, Desa Suwug, Kabupaten Buleleng. The best spline regression model is chosen based on the minimum Generalized Cross Validation (GCV) value. The study shows that the best spline regression model for the data is quadratic

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Suparti, Suparti, and Alan Prahutama. "PEMODELAN REGRESI NONPARAMETRIK MENGGUNAKAN PENDEKATAN POLINOMIAL LOKAL PADA BEBAN LISTRIK DI KOTA SEMARANG." MEDIA STATISTIKA 9, no. 2 (2017): 85. http://dx.doi.org/10.14710/medstat.9.2.85-93.

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Semarang is the provincial capital of Central Java, with infrastructure and economic’s growth was high. The phenomenon of power outages that occurred in Semarang, certainly disrupted economic development in Semarang. Large electrical energy consumed by industrial-scale consumers and households in the San Francisco area, monitored or recorded automatically and presented into a historical data load power consumption. Therefore, this study modeling the load power consumption at a time when not influenced by the use of electrical load (t-1)-th. Modeling using nonparametric regression approach with

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Sundararajan, S., and S. S. Keerthi. "Predictive Approaches for Choosing Hyperparameters in Gaussian Processes." Neural Computation 13, no. 5 (2001): 1103–18. http://dx.doi.org/10.1162/08997660151134343.

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Gaussian processes are powerful regression models specified by parameterized mean and covariance functions. Standard approaches to choose these parameters (known by the name hyperparameters) are maximum likelihood and maximum a posteriori. In this article, we propose and investigate predictive approaches based on Geisser's predictive sample reuse (PSR) methodology and the related Stone's cross-validation (CV) methodology. More specifically, we derive results for Geisser's surrogate predictive probability (GPP), Geisser's predictive mean square error (GPE), and the standard CV error and make a

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NIRMALA YANI, NI WAYAN MERRY, I. GUSTI AYU MADE SRINADI, and I. WAYAN SUMARJAYA. "APLIKASI MODEL REGRESI SEMIPARAMETRIK SPLINE TRUNCATED (Studi Kasus: Pasien Demam Berdarah Dengue (DBD) di Rumah Sakit Puri Raharja)." E-Jurnal Matematika 6, no. 1 (2017): 65. http://dx.doi.org/10.24843/mtk.2017.v06.i01.p149.

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Semiparametric regression is a regression model that includes parametric components and nonparametric components in a model. The regression model in this research is truncated spline semiparametric regression with case studies of patients with Dengue Hemorrhagic Fever (DHF) at Puri Raharja Hospital during the period of January to March 2015. The best regression model estimation is obtained from the selection of optimal knots which has minimum Generalized Cross Validation (GCV) is. Parametric components in this research include age (years), body temperature (0C), platelets and hematocrit (%) as

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Yao, Gang, Jian Jun Zhao, and Jing Jie Sun. "A Research on a Method of Error Separation Based on Wavelet Analysis." Applied Mechanics and Materials 380-384 (August 2013): 3774–77. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3774.

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According to the error character of the systematic error and random error in calibration data, we put forward using wavelet analysis method to the process of separating error. We give the basic principle and method to dispose random error with Wavelet Analysis. When choosing the threshold, we use GCV(Generalized Cross Validation) principle. Then use IA to search the best value of GCV function and realize the separation simulation of random error in the MATLAB. During the selection operation of IA(Immune Algorithm), the expecting propagation probability is computed in order to guarantee the div

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Arghand, Muhammad, and Majid Amirfakhrian. "A Meshless Method Based on the Fundamental Solution and Radial Basis Function for Solving an Inverse Heat Conduction Problem." Advances in Mathematical Physics 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/256726.

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We propose a new meshless method to solve a backward inverse heat conduction problem. The numerical scheme, based on the fundamental solution of the heat equation and radial basis functions (RBFs), is used to obtain a numerical solution. Since the coefficients matrix is ill-conditioned, the Tikhonov regularization (TR) method is employed to solve the resulted system of linear equations. Also, the generalized cross-validation (GCV) criterion is applied to choose a regularization parameter. A test problem demonstrates the stability, accuracy, and efficiency of the proposed method.

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Aydın, Dursun, Bahadır Yüzbaşı, and S. Ejaz Ahmed. "Modified Ridge Type Estimator in Partially Linear Regression Models and Numerical Comparisons." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 7040–53. http://dx.doi.org/10.1166/jctn.2016.5669.

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In this article, we introduce a modified ridge type estimator for the vector of parameters in a partially linear model. This estimator is a generalization of the well-known Speckman’s approach and is based on smoothing splines method. Most important in the implementation of this method is the choice of the smoothing parameter. Many Criteria of selecting smoothing parameters such as improved version of Akaike information criterion (AICc), generalized cross-validation (GCV), cross-validation (CV), Mallows’ Cp criterion, risk estimation using classical pilots (REC) and Bayes information criterion

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Xu, Xiaowei, and Ting Bu. "An Adaptive Parameter Choosing Approach for Regularization Model." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 08 (2018): 1859013. http://dx.doi.org/10.1142/s0218001418590139.

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The choice of regularization parameters is a troublesome issue for most regularization methods, e.g. Tikhonov regularization method, total variation (TV) method, etc. An appropriate parameter for a certain regularization approach can obtain fascinating results. However, general methods of choosing parameters, e.g. Generalized Cross Validation (GCV), cannot get more precise results in practical applications. In this paper, we consider exploiting the more appropriate regularization parameter within a possible range, and apply the estimated parameter to Tikhonov model. In the meanwhile, we obtain

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Arles, Clemensius, Sifriyani Sifriyani, and Fidia Deny Tisna Amijaya. "MODEL NONPARAMETRIC GWR UNTUK IDENTIFIKASI FAKTOR YANG MEMPENGARUHI COD DAS MAHAKAM." STATISTIKA Journal of Theoretical Statistics and Its Applications 21, no. 1 (2021): 5–10. http://dx.doi.org/10.29313/jstat.v21i1.7706.

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ABSTRAKModel Regresi Spline Nonparametrik dengan Pembobot Geografis merupakan pengembangan model regresi nonparametrik untuk data spasial dengan estimator parameter bersifat lokal untuk setiap pengamatan yang di aplikasikan pada data spasial. Data penelitian ini merupakan data sekunder yang diperoleh dari Dinas Lingkungan Hidup Provinsi Kalimantan Timur Samarinda. Tujuan penelitian ini adalah menentukan model pada data Chemical Oxygen Demand (COD) di Daerah Aliran Sungai Mahakam Kalimantan Timur dan untuk mengetahui faktor-faktor apa saja yang mempengaruhi COD di 28 titik pengambilan sampel pa

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ASTUTI, DEWA AYU DWI, I. GUSTI AYU MADE SRINADI, and MADE SUSILAWATI. "PENDEKATAN REGRESI NONPARAMETRIK DENGAN MENGGUNAKAN ESTIMATOR KERNEL PADA DATA KURS RUPIAH TERHADAP DOLAR AMERIKA SERIKAT." E-Jurnal Matematika 7, no. 4 (2018): 305. http://dx.doi.org/10.24843/mtk.2018.v07.i04.p218.

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Nonparametric regression can be applied for some data types one of them is time series data. The technique of this method is called smoothing technique. There are several smoothing techniques however this study used kernel estimator with seven kernel functions in data of rupiah exchange rate to US dollar. The analysis with R shows that by using minimum Generalized Cross Validation (GCV) criteria, seven functions produce various optimal bandwidth value but has similar curves estimation. The conclusion is that by using kernel estimator in time series data support that choosing the optimal bandwi

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Widagdo, Nurhaerunisa, Muhammad Kasim Aidid, and S. Sudarmin. "Multivariate Adaptive Regression Splines pada Kasus Inflasi di Indonesia Tahun 2005-2018." VARIANSI: Journal of Statistics and Its application on Teaching and Research 2, no. 3 (2020): 110. http://dx.doi.org/10.35580/variansiunm14639.

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Abstrak. Kegiatan perekonomian suatu negara dipengaruhi oleh inflasi yang terjadi pada negara tersebut. Tingkat inflasi Indonesia yang fluktuatif, cenderung tidak stabil, mempengaruhi kehidupan sosial dan ekonomi masyarakat. Sehingga penting untuk mengetahui faktor-faktor yang berpengaruh terhadap inflasi serta pemodelan faktor-faktor berpengaruh tersebut dan hubungannya terhadap inflasi. Mengidentifikasi hubungan inflasi dan faktor penyebabnya dilakukan menggunakan pemodelan Multivariate Adaptive Regression Splines (MARS). MARS merupakan jenis regeresi nonparametrik yang menggabungkan prinsip

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Pratiwi, Deni, Lalu Abd Azis Mursy, Muhammad Rizaldi, and Nurul Fitriyani. "Regresi Nonparametrik Kernel Gaussian pada Pemodelan Angka Kelahiran Kasar di Provinsi Nusa Tenggara Barat." EIGEN MATHEMATICS JOURNAL 3, no. 2 (2020): 100. http://dx.doi.org/10.29303/emj.v3i2.78.

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This study aims to model Crude Birth Rates (CBR) in West Nusa Tenggara Province. The nonparametric regression method was used in this research by considering data distribution patterns that do not show a linear relationship between variables. In this case, the kernel nonparametric regression using the Gaussian function and the Nadaraya-Watson estimator. The results showed optimal bandwidths of 0.55542837, 1.29042927, 0.94706041, and 0.92278896 with a value of minimum Generalized Cross-Validation (GCV) of 0.000000000432613511, which was minimized by the simulated annealing algorithm. The result

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ARYATI, NI LUH GEDE SINTA, I. KOMANG GDE SUKARSA, and I. GUSTI AYU MADE SRINADI. "PEMODELAN RATA-RATA LAMA SEKOLAH MENGGUNAKAN PENDEKATAN REGRESI NONPARAMETRIK SPLINE MULTIVARIABLE." E-Jurnal Matematika 10, no. 2 (2021): 53. http://dx.doi.org/10.24843/mtk.2021.v10.i02.p320.

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Mean years school (MYS) is one of the indicators used in calculating the human development index (HDI). The value of MYS Indonesia in 2019 is 8,75 which is still low. Therefore it still needs to be improved. In this research, MYS modeling will be carried out using six factors that are thought to influence MYS. This research uses multivariable spline nonparametric regression to modeling MYS Indonesia in 2019. The best model is selected based on the minimum value of Generalized Cross Validation (GCV). Based on this research, the best model obtained is a linear orde (orde 2) spline model with fou

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DANGIN, NYOMAN KRISHNA PRATIWI, I. GUSTI AYU MADE SRINADI, and I. WAYAN SUMARJAYA. "PEMODELAN KASUS GIZI BURUK PADA BALITA DI PROVINSI BALI TAHUN 2018 MENGGUNAKAN REGRESI SPLINE." E-Jurnal Matematika 10, no. 3 (2021): 148. http://dx.doi.org/10.24843/mtk.2021.v10.i03.p335.

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Malnutrition associated with an unusual condition of the patient's nutritional status because the body weight index and age are not suitable, where body weight should be positively correlated with age. According to data from the Bali Health Department, malnutrition cases found in 2016 is 3,4% while in 2017 it founded 3,8%. This research uses spIine regression with malnutrition cases of children under 5 years old in Bali Province. To compare basis truncated spIine and B-SpIine, this study using the minimum value of Generalized Cross Validation (GCV) and Mean Square Error (MSE) of each basis. B-

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Arashi, M., M. Roozbeh, N. A. Hamzah, and M. Gasparini. "Ridge regression and its applications in genetic studies." PLOS ONE 16, no. 4 (2021): e0245376. http://dx.doi.org/10.1371/journal.pone.0245376.

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With the advancement of technology, analysis of large-scale data of gene expression is feasible and has become very popular in the era of machine learning. This paper develops an improved ridge approach for the genome regression modeling. When multicollinearity exists in the data set with outliers, we consider a robust ridge estimator, namely the rank ridge regression estimator, for parameter estimation and prediction. On the other hand, the efficiency of the rank ridge regression estimator is highly dependent on the ridge parameter. In general, it is difficult to provide a satisfactory answer

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Billings, Stephen D., Garry N. Newsam, and Rick K. Beatson. "Smooth fitting of geophysical data using continuous global surfaces." GEOPHYSICS 67, no. 6 (2002): 1823–34. http://dx.doi.org/10.1190/1.1527082.

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Continuous global surfaces (CGS) are a general framework for interpolation and smoothing of geophysical data. The first of two smoothing techniques we consider in this paper is generalized cross validation (GCV), which is a bootstrap measure of the predictive error of a surface that requires no prior knowledge of noise levels. The second smoothing technique is to define the CGS surface with fewer centers than data points, and compute the fit by least squares (LSQR); the noise levels are implicitly estimated by the number and placement of the centers relative to the data points. We show that bo

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Sauri, Muhammad Sopian, Mustika Hadijati, and Nurul Fitriyani. "Spline and Kernel Mixed Nonparametric Regression for Malnourished Children Model in West Nusa Tenggara." Jurnal Varian 4, no. 2 (2021): 99–108. http://dx.doi.org/10.30812/varian.v4i2.1003.

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Health sector development is essential to improve human life quality, especially in West Nusa Tenggara (NTB) Province. Based on data from the NTB Provincial Health Office from 2011 to 2016, children under five suffering from malnutrition continued to increase, caused by several factors that affected the incident. Therefore, appropriate analysis is needed to model children who suffer from malnutrition in NTB Province in 2016, consisting of 10 districts based on the variables that influence it. The analysis in this study was carried out using a nonparametric regression mixed-model spline truncat

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Mariati, Ni Putu Ayu Mirah, I. Nyoman Budiantara, and Vita Ratnasari. "Combination Estimation of Smoothing Spline and Fourier Series in Nonparametric Regression." Journal of Mathematics 2020 (July 1, 2020): 1–10. http://dx.doi.org/10.1155/2020/4712531.

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So far, most of the researchers developed one type of estimator in nonparametric regression. But in reality, in daily life, data with mixed patterns were often encountered, especially data patterns which partly changed at certain subintervals, and some others followed a recurring pattern in a certain trend. The estimator method used for the data pattern was a mixed estimator method of smoothing spline and Fourier series. This regression model was approached by the component smoothing spline and Fourier series. From this process, the mixed estimator was completed using two estimation stages. Th

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ASTITI, DESAK AYU WIRI, I. WAYAN SUMARJAYA, and MADE SUSILAWATI. "ANALISIS REGRESI NONPARAMETRIK SPLINE MULTIVARIAT UNTUK PEMODELAN INDIKATOR KEMISKINAN DI INDONESIA." E-Jurnal Matematika 5, no. 3 (2016): 111. http://dx.doi.org/10.24843/mtk.2016.v05.i03.p129.

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The aim of this study is to obtain statistics models which explain the relationship between variables that influence the poverty indicators in Indonesia using multivariate spline nonparametric regression method. Spline is a nonparametric regression estimation method that is automatically search for its estimation wherever the data pattern move and thus resulting in model which fitted the data. This study, uses data from survey of Social Economy National (Susenas) and survey of Employment National (Sakernas) of 2013 from the publication of the Central Bureau of Statistics (BPS). This study yiel

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Ramdhani, Zhazha Alifkhamulki, Anna Islamiyati, and Raupong Raupong. "Hubungan Faktor Kolestrol Terhadap Gula Darah Diabetes dengan Spline Kubik Terbobot." ESTIMASI: Journal of Statistics and Its Application 1, no. 1 (2020): 32. http://dx.doi.org/10.20956/ejsa.v1i1.9252.

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Diabetes Mellitus (DM) is often recognized through an increase in a person's blood sugar level. Factors that can affect the increase in blood sugar levels of DM patients one of which is cholesterol. It usually contains the bookkeeping of several types of cholesterol, including LDL and total cholesterol. DM data are assumed to experience heterokedasticity so that in this study analyzed using regression of weighted cubic spline nonparametric. The estimation method used is weighted least square (WLS). This study aims to obtain a weighted cubic spline model on cholesterol based DM data. The select

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Wu, Zemin, Shaofeng Bian, Caibing Xiang, and Yude Tong. "A New Method for TSVD Regularization Truncated Parameter Selection." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/161834.

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The truncated singular value decomposition (TSVD) regularization applied in ill-posed problem is studied. Through mathematical analysis, a new method for truncated parameter selection which is applied in TSVD regularization is proposed. In the new method, all the local optimal truncated parameters are selected first by taking into account the interval estimation of the observation noises; then the optimal truncated parameter is selected from the local optimal ones. While comparing the new method with the traditional generalized cross-validation (GCV) andLcurve methods, a random ill-posed matri

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Xu, Yanchun, Haiting Xia, Chao Tan, Zhenhua Li, and Lu Mi. "Research on Partial Discharge De-Noising for Transformer Based on Synchro-Squeezed Continuous Wavelet Transform." Fluctuation and Noise Letters 19, no. 02 (2020): 2050021. http://dx.doi.org/10.1142/s0219477520500212.

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Traditional time-frequency methods for partial discharge (PD) de-noising have some limitations such as low time-frequency resolution, single de-noising type and poor readability. In this paper, a novel de-noising algorithm based on synchro-squeezed continuous wavelet transform (CWT) is adopted to filter out narrowband noise and white noise. The synchro-squeezed CWT algorithm is designed to redistribute the time-frequency domain and to distinguish the signal from the noise carefully as a high-rate time-frequency analysis. High-order statistics is employed to pre-process the polluted PD signal.

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Gao, Wei, Kaiping Yu, and Ying Wu. "A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification." Shock and Vibration 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/7328969.

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According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF) is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem. Secondly, the quotient function method (QFM) is proposed to select the optimal regularization parameter based on the quadratic programming theory. For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are t

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De-Graft Acquah, Henry, and Lawrence Acheampong. "Comparing parametric and semiparametric error correction models for estimation of long run equilibrium between exports and imports." Applied Studies in Agribusiness and Commerce 11, no. 1-2 (2017): 19–23. http://dx.doi.org/10.19041/apstract/2017/1-2/3.

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This paper introduces the semiparametric error correction model for estimation of export-import relationship as an alternative to the least squares approach. The intent is to demonstrate how semiparametric error correction model can be used to estimate the relationship between Ghana’s export and import within the context of a generalized additive modelling (GAM) framework. The semiparametric results are compared to common parametric specification using the ordinary least squares regression. The results from the semiparametric and parametric error correction models (ECM) indicate that the error

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WULANDARY, SEPTIE, and DRAJAT INDRA PURNAMA. "PERBANDINGAN REGRESI NONPARAMETRIK KERNEL DAN B-SPLINES PADA PEMODELAN RATA-RATA LAMA SEKOLAH DAN PENGELUARAN PERKAPITA DI INDONESIA." Jambura Journal of Probability and Statistics 1, no. 2 (2020): 89–97. http://dx.doi.org/10.34312/jjps.v1i2.7501.

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Analisis regresi merupakan salah satu alat statistik yang banyak digunakan untuk mengetahui hubungan antara dua variabel acak atau lebih. Metode penaksiran model regresi terbagi atas regresi parametrik dan nonparametrik. Penelitian ini bertujuan menganalisis pola hubungan pengeluaran perkapita terhadap rata-rata lama sekolah di Indonesia tahun 2018 melalui perbandingan regresi nonparametrik, yaitu regresi kernel dan spline. Regresi kernel yang digunakan adalah regresi kernel dengan metode penaksir Nadaraya-Watson (NWE), sedangkan regresi spline yang digunakan adalah B-Splines. Berdasarkan nila

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Nur Wisisono, Intaniah Ratna, Ade Irma Nurwahidah, and Yudhie Andriyana. "Regresi Nonparametrik dengan Pendekatan Deret Fourier pada Data Debit Air Sungai Citarum." Jurnal Matematika "MANTIK" 4, no. 2 (2018): 75–82. http://dx.doi.org/10.15642/mantik.2018.4.2.75-82.

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River discharge is one of the factors that affect the occurrence of floods. It varies over time and hence we need to predict the flood risk. Since the plot of the data changes periodically showing a sines and cosines pattern, a nonparametric technique using Fourier series approach may be interesting to be applied. Fourier series can be estimated using OLS (Ordinary Least Square). In a Fourier series, nonparametric regression the level of subtlety of its function is determined by their bandwidth (K). Optimal bandwidth determined using the GCV (Generalized Cross Validation) method. From the calc

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He, Xiaowei, Jimin Liang, Xiaochao Qu, Heyu Huang, Yanbin Hou, and Jie Tian. "Truncated Total Least Squares Method with a Practical Truncation Parameter Choice Scheme for Bioluminescence Tomography Inverse Problem." International Journal of Biomedical Imaging 2010 (2010): 1–11. http://dx.doi.org/10.1155/2010/291874.

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In bioluminescence tomography (BLT), reconstruction of internal bioluminescent source distribution from the surface optical signals is an ill-posed inverse problem. In real BLT experiment, apart from the measurement noise, the system errors caused by geometry mismatch, numerical discretization, and optical modeling approximations are also inevitable, which may lead to large errors in the reconstruction results. Most regularization techniques such as Tikhonov method only consider measurement noise, whereas the influences of system errors have not been investigated. In this paper, the truncated

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Padatuan, Aprianti Boma, Sifriyani Sifriyani, and Surya Prangga. "PEMODELAN ANGKA HARAPAN HIDUP DAN ANGKA KEMATIAN BAYI DI KALIMANTAN DENGAN REGRESI NONPARAMETRIK SPLINE BIRESPON." BAREKENG: Jurnal Ilmu Matematika dan Terapan 15, no. 2 (2021): 283–96. http://dx.doi.org/10.30598/barekengvol15iss2pp283-296.

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Penelitian ini menggunakan model regresi nonparametrik birespon dengan pendekatan spline truncated. Model tersebut digunakan untuk menyelesaikan permasalahan analisis regresi yang bentuk kurvanya tidak diketahui. Pendekatan spline truncated memiliki fungsi polinomial tersegmen yang memberikan sifat fleksibilitas. Data yang digunakan dalam penelitian ini terdiri dari dua variabel respon yaitu Angka Harapan Hidup (AHH) dan Angka Kematian Bayi (AKB) di Pulau Kalimantan. Tujuan penelitian adalah untuk menentukan model regresi nonparametrik spline truncated birespon pada data AHH dan AKB dan menget

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DEWI, I. GUSTI AYU MADE VALENTINA, I. GUSTI AYU MADE SRINADI, and MADE SUSILAWATI. "PEMODELAN KASUS PNEUMONIA PADA BALITA DI PROVINSI BALI MENGGUNAKAN METODE REGRESI NONPARAMETRIK B-SPLINE." E-Jurnal Matematika 9, no. 3 (2020): 197. http://dx.doi.org/10.24843/mtk.2020.v09.i03.p299.

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Pneumonia is an inflammatory lung disease caused by bacterium Streptococcus pneumonia, Chlamydophila pneumonia bacteria, influenza virus, and fungi. Bali Provincial Health Service data in 2018 shows that one of the diseases that causes many deaths in children under five is pneumonia. This study aims to model the number of pneumonia cases in children under five in Bali Province in 2018 with six research variables, namely percentage of low birth weight, percentage of coverage of infants who receive vitamin A, percentage of infants who receive exclusive breastfeeding, percentage of under-five hea

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Wei, Xiu Lei, Rui Lin Lin, Shu Yong Liu, and Qiang Wang. "Improvement of Chaotic Signals De-Noising with the Self-Optimizing Method of Wavelet Threshold." Applied Mechanics and Materials 556-562 (May 2014): 4950–54. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4950.

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For the purpose of improving adaptive performance of chaotic signals de-noising with wavelet transform, a method of Memetic-algorithm-based adaptive wavelet de-noising (MAWD) is presented. The MAWD based on generalized cross validation (GCV) is competent to obtain the global optimum thresholds and to raise the efficiency of adaptive searching computation. The de-noising results of simulative Lorenz time series are presented. The results show that the chaotic signals de-noised by MAWD can remove the white noise more effectively than the signals de-noised by using standard soft threshoding metho

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Su, Liyun, and Chenlong Li. "Local Functional Coefficient Autoregressive Model for Multistep Prediction of Chaotic Time Series." Discrete Dynamics in Nature and Society 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/329487.

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A new methodology, which combines nonparametric method based on local functional coefficient autoregressive (LFAR) form with chaos theory and regional method, is proposed for multistep prediction of chaotic time series. The objective of this research study is to improve the performance of long-term forecasting of chaotic time series. To obtain the prediction values of chaotic time series, three steps are involved. Firstly, the original time series is reconstructed inm-dimensional phase space with a time delayτby using chaos theory. Secondly, select the nearest neighbor points by using local me

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Ren, ChunPing, NengJian Wang, and ChunSheng Liu. "Identification of Random Dynamic Force Using an Improved Maximum Entropy Regularization Combined with a Novel Conjugate Gradient." Mathematical Problems in Engineering 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/9125734.

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We propose a novel mathematical algorithm to offer a solution for the inverse random dynamic force identification in practical engineering. Dealing with the random dynamic force identification problem using the proposed algorithm, an improved maximum entropy (IME) regularization technique is transformed into an unconstrained optimization problem, and a novel conjugate gradient (NCG) method was applied to solve the objective function, which was abbreviated as IME-NCG algorithm. The result of IME-NCG algorithm is compared with that of ME, ME-CG, ME-NCG, and IME-CG algorithm; it is found that IME

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Matdoan, Muhammad Yahya, A. M. Balami, and M. W. Talakua. "PEMODELAN REGRESI NONPARAMETRIK SPLINE TRUNCATED PADA FAKTOR-FAKTOR YANG MEMPENGARUHI PERTUMBUHAN EKONOMI DI PROVINSI MALUKU." VARIANCE : Journal of Statistics and Its Applications 1, no. 1 (2019): 27–37. http://dx.doi.org/10.30598/variancevol1iss1page27-37.

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Economic growth is a benchmark for the success of a region's development, especially in the economic field. The purpose of economic development in an area is basically to improve the welfare and prosperity of the community. Economic growth in Maluku Province experienced a positive increase. However, there is still a disparity between districts/cities in Maluku Province, which has an impact on increasing unemployment and an increasingly poor population. This is inseparable from the influencing factors so that it can be precisely done by modeling these factors using the truncated nonparametric s

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Smerdon, Jason E., Alexey Kaplan, and Diana Chang. "On the Origin of the Standardization Sensitivity in RegEM Climate Field Reconstructions*." Journal of Climate 21, no. 24 (2008): 6710–23. http://dx.doi.org/10.1175/2008jcli2182.1.

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Abstract The regularized expectation maximization (RegEM) method has been used in recent studies to derive climate field reconstructions of Northern Hemisphere temperatures during the last millennium. Original pseudoproxy experiments that tested RegEM [with ridge regression regularization (RegEM-Ridge)] standardized the input data in a way that improved the performance of the reconstruction method, but included data from the reconstruction interval for estimates of the mean and standard deviation of the climate field—information that is not available in real-world reconstruction problems. When

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W, Anies Yulinda, Trias Novia L., Melati Tegarina, and Nur Chamidah. "ANALISIS PENGARUH ANGKA KEMATIAN BAYI TERHADAP ANGKA HARAPAN HIDUP DI PROVINSI JAWA TIMUR BERDASARKAN ESTIMATOR LEAST SQUARE SPINE." Contemporary Mathematics and Applications (ConMathA) 1, no. 1 (2019): 56. http://dx.doi.org/10.20473/conmatha.v1i1.14775.

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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 m

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Li, Minzong, and Huancai Lu. "Reconstruction of Interior Sound Fields of Vibrating Shells with an Open Spherical Microphone Array." Journal of Computational Acoustics 24, no. 04 (2016): 1650013. http://dx.doi.org/10.1142/s0218396x16500132.

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Spherical acoustic holography was utilized to reconstruct the interior sound field of an enclosed space with vibrating boundaries using an open spherical microphone array. The interior sound fields of vibrating shells, including a pulsating shell, a [Formula: see text]-axis oriented oscillating shell, a partially vibrating shell and a point-excited vibrating shell, were reconstructed, and numerical simulations were carried out to examine the impact of reconstruction parameters, the radius of the microphone array, the number of microphones, the distribution of microphones on the array surface,

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Hidayati, Lilik, Nur Chamidah, and I. Nyoman Budiantara. "ESTIMASI SELANG KEPERCAYAAN NILAI UJIAN NASIONAL BERBASIS KOMPETENSI BERDASARKAN MODEL REGRESI SEMIPARAMETRIK MULTIRESPON TRUNCATED SPLINE." MEDIA STATISTIKA 13, no. 1 (2020): 92–103. http://dx.doi.org/10.14710/medstat.13.1.92-103.

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Confidence interval estimation is important in statistical inference for the parameters of the regression model, but the theory of confidence interval estimation for multi-response semiparametric regression model parameters based on the truncated spline estimator has not been examined. In this study, we estimate the confidence interval of the multi-response semiparametric regression model based on the truncated spline estimator by using pivotal quantity method with the central limit theorem approach. This confidence interval theory is applied to data of competency-based national exam (UNBK) sc

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