scholarly journals Pemodelan Persentase Penduduk Miskin Kabupaten/Kota di Provinsi Jawa Barat dengan Pendekatan Regresi Nonparametrik Spline Truncated

2021 ◽  
Vol 14 (1) ◽  
pp. 24-29
Author(s):  
Andrea Tri Rian Dani ◽  
Ludia Ni'matuzzahroh
Keyword(s):  
Least Squares ◽  
Cross Validation ◽  
Ordinary Least Squares ◽  
Generalized Cross Validation

Estimator Spline Truncated adalah salah satu pendekatan dalam regresi nonparametrik yang dapat digunakan ketika pola hubungan antara variabel respon dan variabel prediktor tidak diketahui dengan pasti polanya. Estimator Spline Truncated memiliki fleksibilitas yang tinggi dalam proses pemodelan. Pada penelitian ini  bertujuan untuk memodelkan persentase penduduk miskin Kabupaten/Kota di Provinsi Jawa Barat dengan menggunakan model regresi nonparametrik estimator Spline Truncated. Metode estimasi yang digunakan adalah Ordinary Least Squares (OLS). Kriteria kebaikan model regresi nonparametrik yang digunakan adalah Generalized Cross-Validation (GCV). Berdasarkan hasil analisis, diperoleh model terbaik dari regresi nonparametrik Spline Truncated, yaitu model dengan 3 titik knot, dimana diperoleh nilai GCV minimum sebesar 2.14. Berdasarkan hasil pengujian hipotesis, baik secara simultan maupun parsial, diketahui bahwa variabel prediktor yang digunakan pada penelitian ini, berpengaruh signifikan terhadap persentase penduduk miskin, dengan nilai koefisien determinasi sebesar 95.33%.

Automatic blind deconvolution with Toeplitz-structured sparse total least squares

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. V345-V357 ◽  
Author(s):  
Nasser Kazemi
Keyword(s):  
Least Squares ◽  
Cross Validation ◽  
Blind Deconvolution ◽  
Real Data ◽  
Total Least Squares ◽  
Data Matrix ◽  
Seismic Survey ◽  
Structural Constraints ◽  
Generalized Cross Validation ◽  
Free Data

Given the noise-corrupted seismic recordings, blind deconvolution simultaneously solves for the reflectivity series and the wavelet. Blind deconvolution can be formulated as a fully perturbed linear regression model and solved by the total least-squares (TLS) algorithm. However, this algorithm performs poorly when the data matrix is a structured matrix and ill-conditioned. In blind deconvolution, the data matrix has a Toeplitz structure and is ill-conditioned. Accordingly, we develop a fully automatic single-channel blind-deconvolution algorithm to improve the performance of the TLS method. The proposed algorithm, called Toeplitz-structured sparse TLS, has no assumptions about the phase of the wavelet. However, it assumes that the reflectivity series is sparse. In addition, to reduce the model space and the number of unknowns, the algorithm benefits from the structural constraints on the data matrix. Our algorithm is an alternating minimization method and uses a generalized cross validation function to define the optimum regularization parameter automatically. Because the generalized cross validation function does not require any prior information about the noise level of the data, our approach is suitable for real-world applications. We validate the proposed technique using synthetic examples. In noise-free data, we achieve a near-optimal recovery of the wavelet and the reflectivity series. For noise-corrupted data with a moderate signal-to-noise ratio (S/N), we found that the algorithm successfully accounts for the noise in its model, resulting in a satisfactory performance. However, the results deteriorate as the S/N and the sparsity level of the data are decreased. We also successfully apply the algorithm to real data. The real-data examples come from 2D and 3D data sets of the Teapot Dome seismic survey.

scholarly journals The L-Curve Criterion as a Model Selection Tool in PLS Regression

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Abdelmounaim Kerkri ◽  
Jelloul Allal ◽  
Zoubir Zarrouk
Keyword(s):  
Model Selection ◽  
Least Squares ◽  
Cross Validation ◽  
Real Data ◽  
Ordinary Least Squares ◽  
Pls Regression ◽  
Selection Tool ◽  
Reliable Model ◽  
Mean Squared Prediction Error ◽  
Squared Prediction Error

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 application on both simulated and real data. The application shows how this criterion generally outperforms cross validation and generalized cross validation (GCV) in mean squared prediction error and computational efficiency.

Least Squares Model Averaging Based on Generalized Cross Validation

2021 ◽  
Vol 37 (3) ◽  
pp. 495-509
Author(s):  
Xin-min Li ◽  
Guo-hua Zou ◽  
Xin-yu Zhang ◽  
Shang-wei Zhao
Keyword(s):  
Least Squares ◽  
Cross Validation ◽  
Model Averaging ◽  
Generalized Cross Validation

PENGARUH STRUKTUR KEPEMILIKAN BANK TERHADAP KINERJA UNIT USAHA SYARIAH PADA BANK DI INDONESIA

2018 ◽  
Vol 1 (2) ◽  
pp. 25-32
Author(s):  
Hafidzah Nurjannah ◽  
Yul Efnita ◽  
Eva Sundari
Keyword(s):  
Least Squares ◽  
Firm Size ◽  
Ordinary Least Squares

Penelitian ini bertujuan untuk menganalisa pengaruh secara signifikan baik partial maupun simultan pada variabel kepemilikan bank, simpanan (DPK), rasio pinjaman terhadap simpanan (LDR) dan rasio kecukupan modal (CAR), Non Performing Loan (NPL) dan ukuran perusahaan terhadap profitabilitas (ROA) pada bank yang memiliki Unit Usaha Syariah (UUS) baik itu pada Bank Pembangunan Daerah (BPD) maupun Bank Swasta. Populasi dan sampel terdiri dari 24 UUS milik Bank Pembangunan Daerah (BPD) dan Bank Swasta. Dari ke 24 bank tersebut, hanya 18 bank yang dipilih menjadi sampel. Bank-bank tersebut adalah 7 Bank Swasta dan 11 Bank Pembangunan Daerah. Periode penelitian ini adalah 2010-2014. Data diambil dari laporan tahunan bank. Penelitian ini menggunakan data panel dan pooled Ordinary Least Squares (OLS). Hasil penelitian menunjukkan UUS milik Bank Pembangunan Daerah lebih baik daripada Bank Swasta. Hal ini disebabkan beberapa faktor. Pertama, pinjaman hanya untuk pejabat pemerintah daerah di mana pembayaran pinjaman melalui pengurangan gaji, sehingga kemungkinan tidak dapat membayar pinjaman sangat rendah meskipun situasi ekonomi tidak stabil. Kedua, karena Bank Pembangunan Daerah menyediakan layanan hanya untuk lokal saja, sehingga memiliki pengetahuan khusus tentang daerah tersebut. Sehingga akan memungkinkan nasabah menilai penerapan pinjaman dan mengidentifikasi pinjaman yang memenuhi syarat. Ketiga, kinerja Bank Pembangunan Daerah yang diawasi oleh pemerintah daerah lebih intensif. Kata Kunci : Hedging, Laverage, Cash Ratio, Firm Size, Bank Syariah.

The antecedents of corporate social and environmental responsibility discourse in Pakistan: Multiple theoretical perspectives

2019 ◽  
Author(s):  
Muhammad Farhan Basheer ◽  
Saqib Muneer ◽  
Muhammad Atif ◽  
Zubair Ahmad
Keyword(s):  
Institutional Theory ◽  
Least Squares ◽  
Agency Theory ◽  
Stakeholder Theory ◽  
Fixed Effects ◽  
Ordinary Least Squares ◽  
Environmental Responsibility ◽  
Legitimacy Theory ◽  
Discourse Practices ◽  
Corporate Social

The primary purpose of the study is to explore the antecedents of corporate social and environmental responsibilities discourse practices in Pakistan. The industry sensitivity, government shareholding, block holder ownership, print media coverage, environmental monitoring programs, and strategic posture are examined as antecedents of corporate social and environmental responsibility practices. A multidimensional theoretical perspective namely stakeholder theory (ST), institutional theory (IT), agency theory (PAT), and legitimacy theory (LT) is used to conceptualize the phenomena. All the four of perspective theories (positive accounting theory, legitimacy theory, stakeholder theory, and institutional theory) claim that there are ‘pressures’ that impact the organization. How much ‘pressures’ are recognized, managed or satisfied differs from one perspective of theory to the other. To estimate the data, this study uses three sets of panel data models, i.e., the pooled ordinary least squares model (POLS) or constant coefficients model, fixed effects (FEM or least squares dummy variable/LSDV model) and random-effects models. The final sample is comprising of 173 firms over eight years from 2011 to 2017. The firms listed in PSX are included in the sample. Overall the findings of the study have shown agreement with the proposed results. However, the study has provided more support to the institutional theory and stakeholder theory. Keywords: Corporate Social Responsibility, Stakeholders Theory, Agency Theory, Pakistan

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