scholarly journals PENERAPAN REGRESI NONPARAMETRIK KERNEL DAN SPLINE DALAM MEMODELKAN RETURN ON ASSET (ROA) BANK SYARIAH DI INDONESIA

2021 ◽  
Vol 14 (2) ◽  
pp. 115
Author(s):  
Putri Indi Rahayu ◽  
Pardomuan Robinson Sihombing
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Interest Rates ◽  
Nonparametric Regression ◽  
Smooth Curve ◽  
Spline Regression ◽  
Return On Assets ◽  
B Splines ◽  
Regression Methods ◽  
Regression Curves

Sharia Bank Return On Assets (ROA) modeling in Indonesia in 2018 aims to analyze the relationship pattern of Retturn On Assets (ROA) with interest rates. The analysis that is often used for modeling is regression analysis. Regression analysis is divided into two, namely parametric and nonparametric. The most commonly used nonparametric regression methods are kernel and spline regression. In this study, the nonparametric regression used was kernel regression with the Nadaraya-Watson (NWE) estimator and Local Polynomial (LPE) estimator, while the spline regression was smoothing spline and B-splines. The fitting curve results show that the best model is the B-splines regression model with a degree of 3 and the number of knots 5. This is because the B-splines regression model has a smooth curve and more closely follows the distribution of data compared to other regression curves. The B-splines regression model has a determination coefficient of R ^ 2 of 74.92%,%, meaning that the amount of variation in the ROA variable described by the B-splines regression model is 74.92%, while the remaining 25.8% is explained by other variables not included in the model.

Spline Nonparametric Regression Model for Local Revenue in Central Sulawesi

2021 ◽  
Vol 1 (2) ◽  
pp. 31-37
Author(s):  
Mohammad Fajri ◽  
Eka Rizky Wulansari ◽  
Ayu Anggraeni ◽  
Mufitatul Annisa
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Nonparametric Regression ◽  
Local Governments ◽  
Economic Resources ◽  
Spline Regression ◽  
Nonparametric Regression Model ◽  
Local Revenue ◽  
Tax Levies ◽  
Central Sulawesi

Local Own-source Revenue (LOR) is all regional revenue that comes from the region's original economic resources. It is very important to identify it by researching and determining the Regional Local Own-source Revenue (LOR) by properly researching and managing the source of revenue so as to provide maximum results. Central Sulawesi Province itself has Local Own-source Revenue (LOR) in the Regional Revenue and Expenditure Budget of the 2018 Budget Year has reached Rp1 trillion. The increase or decrease in growth of local revenue is influenced by the amount and type of tax, levies collected by local governments and the lack of incentives for the management apparatus to carry out tax collection and levies. This study uses spline regression analysis because the data of the Local Own-source Revenue (LOR) in Central Sulawesi in 2018 does not have a pattern so that it fits perfectly with that method. Then after processing the data obtained the results of spline nonparametric regression modeling using the optimal knots point obtained from the minimum GCV value. The best spline nonparametric regression model is written as follow . It can be concluded that in Central Sulawesi in 2018 the lowest Local Own-source Revenue (LOR) value was Banggai Laut Regency with 21,776 billion rupiahs and the highest Local Own-source Revenue (LOR) value was Palu City at 267,402 billion rupiahs.

VARIABLE SELECTION IN NONPARAMETRIC REGRESSION MODEL

2004 ◽  
Vol 11 (02) ◽  
pp. 141-161
Author(s):  
K. B. KULASEKERA ◽  
JAVIER OLAYA
Keyword(s):  
Regression Model ◽  
Nonparametric Regression ◽  
Selection Process ◽  
Asymptotic Properties ◽  
Intermediate Step ◽  
Forward Selection ◽  
Nonparametric Regression Model ◽  
Regression Curves ◽  
Formal Test ◽  
Candidate Variable

A new procedure is proposed for deciding whether a candidate variable is significant in a general nonparametric regression model with independent covariates. A forward selection process is conducted using a formal test of equality of regression curves at each stage. The proposed procedure does not require multidimensional smoothing at any intermediate step. Asymptotic properties are given. Some simulation results and a real application are given.

scholarly journals Pemodelan Pengaruh Imunisasi DPT Terhadap Angka Kematian Bayi di Jawa Timur Tahun 2016 Menggunakan Pendekatan Regresi Nonparametrik Spline

2019 ◽  
Vol 12 (1) ◽  
pp. 26-31
Author(s):  
Harun Al Azies ◽  
Dea Trishnanti
Keyword(s):  
Regression Analysis ◽  
Nonparametric Regression ◽  
Mortality Rates ◽  
Behavior Patterns ◽  
Spline Regression ◽  
Nonparametric Regression Model ◽  
Live Births ◽  
Linear Spline ◽  
Regression Approach ◽  
Type 3

East Java is one of the provinces with a high IMR level. Based on the District / City report in East Java, in 2006 it was 0.035 live births and became 0.0032 live births in 2008. Identification of factors that influence both indicators correctly can be done by modeling, namely by nonparametric regression analysis. The nonparametric regression approach used is Spline, with its strengths the model tends to look for estimates wherever the data moves. This is because there is a knot point which is a joint fusion point which indicates a change in data behavior patterns. Based on the results of analysis and discussion using Spline analysis, it is known that the factors that influence the incidence of IMR in East Java are toddlers receiving type 3 DPT immunization. The best Spline nonparametric regression model is a linear Spline model with three point knots. The GCV value produced was 51.34. Factors of children under five obtained immunizations affecting infant mortality rates in districts / cities in East Java in 2016. This research still uses linear spline regression program with a combination of one, two, and three knots with R square of 65.92%. The need to develop programs into quadratic and cubic orders using a combination of knots. Jawa Timur merupakan salah satu provinsi dengan tingkat AKB yang tinggi. Berdasarkan laporan Kabupaten/Kota di Jawa Timur, pada tahun 2006 sebesar 0,035 kelahiran hidup dan menjadi 0,0032 kelahiran hidup pada tahun 2008. Jika suatu daerah dengan AKB yang tinggi, maka terdapat kemungkinan bahwa daerah sekitarnya akan memiliki beban AKB yang sama pula. Identifikasi faktor-faktor yang mempengaruhi kedua indikator secara tepat dapat dilakukan dengan pemodelan, yaitu dengan analisis regresi nonparametrik. Pendekatan regresi nonparametric yang digunakan adalah Spline, dengan kelebihannya model cenderung mencari estimasinya kemanapun data tersebut bergerak. Hal ini dikarenakan terdapat titik knot yang merupakan titik perpaduan bersama yang menunjukkan terjadinya perubahan pola perilaku data. Berdasarkan hasil analisis dan pembahasan dengan menggunakan analisis Spline diketahui bahwa faktor yang berpengaruh terhadap kejadian AKB di Jawa Timur adalah balita memperoleh imunisasi DPT tipe 3. Model regresi nonparametrik Spline terbaik adalah model Spline linear dengan tiga titik knot. Nilai GCV yang dihasilkan adalah 51,34. Faktor balita memperoleh imunisasi mempengaruhi angka kematian bayi di kabupaten/kota di Jawa Timur pada tahun 2016. Penelitian ini masih menggunakan program regresi spline linier dengan kombinasi satu, dua, dan tiga knot dengan R square sebesar 65,92%. Perlu adanya pengembangan program menjadi orde kuadratik dan kubik dengan menggunakan kombinasi knot.    

scholarly journals MODEL REGRESI NONPARAMETRIK SPLINE TRUNCATED PADA JUMLAH KASUS TUBERKULOSIS DI PROVINSI BALI TAHUN 2016

2018 ◽  
Vol 7 (3) ◽  
pp. 211 ◽  
Author(s):  
NI PUTU RINA ANGGRENI ◽  
NI LUH PUTU SUCIPTAWATI ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Regression Model ◽  
Nonparametric Regression ◽  
Spline Function ◽  
Cross Validation ◽  
Spline Regression ◽  
Point Selection ◽  
Polynomial Models ◽  
The Government ◽  
High Flexibility

Tuberculosis is a contagious disease caused by Mycobacterium tuberculosis. Based on data from the health office of Bali Province, in 2015 tuberculosis cases found 0,96%, while in 2016 tuberculosis cases increase to 1,05%. This research used truncated spline nonparametric regression to model tuberculosis cases in Bali Province in 2016. This method was used because truncated spline has high flexibility compared to other polynomial models. The truncated spline function has a connecting point called knots. The best estimation of truncated spline regression model is obtained from optimal knot point selection by calculating minimum generalized cross validation. The estimated truncated model is linear with one knot point with determination coefficient equals to 70,48 %. In addition, it is also found in order to reduce tuberculosis cases the government of Bali Province should increase percentage of family who lives clean and healthy.

Analisis Rasio Keuangan dan Makro Ekonomi Untuk Memprediksi Kondisi Financial Distress Perusahaan Subsektor Makanan & Minuman Yang Terdaftar di Bursa Efek Indonesia Tahun 2015-2019

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Febriani Kala’
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Interest Rates ◽  
Analytical Method ◽  
Financial Distress ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Return On Assets ◽  
Current Ratio ◽  
Leverage Ratio

This study aims to determine the effect of financial and macroeconomic ratios on the company's financial distress. In this study, the financial ratios used are the liquidity ratio with the proxy current ratio (CR), the leverage ratio with the proxy debt to assets ratio (DAR), and the profitability ratio with the proxy for return on assets (ROA). Meanwhile, the macro economy is measured by inflation and interest rates. The sample in this study is the food & beverage sub-sector companies listed on the Indonesia Stock Exchange in 2015-2019. The sampling technique used purposive sampling and obtained 17 companies with 5 years of observation so that there were 85 total observations. The analytical method used is logistic regression analysis using the SPSS version 23 program. The results show that the leverage ratio (DAR) has a positive and significant effect on financial distress, the profitability ratio (ROA) has a negative and significant effect on financial distress, while the liquidity ratio (CR) and macroeconomics as measured by inflation and interest rates have a positive but insignificant effect. against financial distress.

Determinants Of Capital Structure For Multinational And Domestic Companies In India: Panel Data Regression Model

2019 ◽  
Vol 118 (7) ◽  
pp. 147-154
Author(s):  
K. Maheswari ◽  
Dr. J. Gayathri ◽  
Dr. M. Babu ◽  
Dr.G. Indhumathi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Regression Model ◽  
Business Risk ◽  
Return On Assets ◽  
Panel Data Regression ◽  
Data Regression ◽  
Return On Capital ◽  
Domestic Companies ◽  
The Capital Structure

The capital structure refers to the components of capital needed to establish and expand its business activities. The study was made with an objective to examine the determinants of capital structure of multinational and domestic companies listed in S&P BSE automobile sector. The study concluded that there is significant impact on capital structure determinants such as size, business risk, non debt shield tax, return on assets, tangibility, profit, return on capital employed and liquidity on the capital structure of multinational and domestic companies of Indian Automobile Sector.  

PENGARUH LEVERAGE, LIKUIDITAS, DAN UKURAN PERUSAHAAN TERHADAP PROFITABILITAS (STUDI KASUS PADA PERUSAHAAN SUB SECTOR REAL ESTATE AND PROPERTY DI BURSA EFEK INDONESIA PERIODE 2015-2018)

2020 ◽  
Vol 4 (02) ◽  
Author(s):  
Pingkan Saraswati
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Real Estate ◽  
Linear Regression Analysis ◽  
T Test ◽  
Company Size ◽  
Return On Assets ◽  
F Test ◽  
Sample Technique ◽  
A Company

Profitabilitya has significance for theecompany because it is one of the bases for evaluating the condition of a company. The level off profitability describes the ecompany's performance as seen from the company's ability to generate profits. Profitability in this study is calculated by return on assets (ROA) because it can show how the company's performance is nseenn from the overall use of assets owned by the company in generating profits. Thissstudyyaims to examine the leverage, liquidity, and size off thee company yaffect the eprofitability. The ssampling ttechniqueu used in this study wass purposivee samplingg, which issaa sample technique ethat uses certain ncriteria.. There earee16 companies ethat are sampled in this sstudy.mThe nanalysiss techniquee usedd is multiplee linearr regressionn using SPSS version 22. Multiplee linear regression analysis susess the eclassicc assumption ntest, nincluding mthe nnormality ntest, multicollonityy test,,heteroscedasticityytest,, and dautocorrelationn test.m Tootestttheevariablessused theecoefficient of determination test, t-test, f-test. The results of this study indicate that there is no significant effect on the variable leverage on profitability. Liquidity hass a positivee effectt onn profitability. There eis snoo significantt effectt off thee Company Size variablee on nthee profitability variable..

Parent-offspring regression in meadow bromegrass (Bromus riparius Rehm.): Evaluation of two methodologies on heritability estimates

2004 ◽  
Vol 84 (1) ◽  
pp. 125-127
Author(s):  
Marcelo R. A. de Araujo ◽  
B. E. Coulman
Keyword(s):  
Regression Analysis ◽  
Block Design ◽  
Covariance Analysis ◽  
Regression Estimate ◽  
Regression Methods ◽  
Randomized Block Design ◽  
Bromus Riparius ◽  
Heritability Estimates ◽  
Analysis Error ◽  
Meadow Bromegrass

To determine the nature and extent of inflation of estimates of heritabilities by parent-offspring regression methods, 40 clones of meadow bromegrass (Bromus riparius Rehm.) and their half-sib progenies were studied in completely randomized block design trials, with six replications in Saskatoon and Melfort, Canada. Clones and progenies were evaluated for dry matter yield, seed yield, plant height, fertility index and harvest index. The results of the analysis showed a consistent inflation of heritability estimates derived from the simple parent-offspring regression, when compared to the regression estimate by variance-covariance analysis. The two methods successfully removed the environmental covariances from the estimates. However, in the simple regression analysis, error covariance was not removed from the numerat or; therefore, heritabilities estimated by this methodology were higher than those estimated by the variance-covariance method. It was concluded that estimates derived from variance-covariance analysis provide less biased estimates of heritability. Key words: Regression analysis, heritability, meadow bromegrass

THE CURRENT TRENDS AND FACTORS IN THE DEVELOPMENT OF MORTGAGE HOUSING LENDING IN RUSSIA

2020 ◽  
Vol 6 (4) ◽  
pp. 320-333
Author(s):  
Natalia A. BABURINA ◽  
Alexey G. KUTSEV ◽  
Daria D. Mukhametzianova ◽  
Lilia A. Kharitonova
Keyword(s):  
Regression Analysis ◽  
Dynamic Analysis ◽  
Interest Rates ◽  
Residential Buildings ◽  
Weighted Average ◽  
Real Estate Market ◽  
Mortgage Lending ◽  
Russian Scientific ◽  
Statistical Dynamic ◽  
Lending Institutions

The presented work contributes to the development of the studies evaluating the key determinants of mortgage housing lending development in Russia. Despite a relatively well-developed body of research in the field of mortgage housing lending, devoted to revealing the essence, functional purpose, and implementation mechanism, the works, aimed at identifying the factors influencing its development in the current economic environment in Russia, are under-represented in the Russian scientific field. This study aims to assess the dynamics of mortgage housing lending in the contemporary economic conditions and to identify the determinants of its defining. The research methodology is based on the use of statistical dynamic analysis and correlation-regression analysis. The work is based on the application of methods of statistical dynamic analysis and correlation-regression analysis. Assessment of the dynamics has shown the general trend towards an increase in the volume of mortgage housing loans. However, some periods have been noted to have a negative dynamic primary related to the negative external environment and stagnation of the economy, due to the COVID-19 pandemic. Additionally, this article presents the assessment of the qualitative indicators characterizing the level of penetration and the degree of aggressiveness of lending institutions’ policies on housing mortgage lending. The authors have built a panel data model that has allowed identifying the key determinants of the development of residential mortgage lending in Russia. The results have revealed that the state of the mortgage lending sector in Russia is influenced by such factors, as the commissioning of residential buildings, the cost in the primary real estate market, weighted average interest rates, and the unemployment rate.

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