scholarly journals Spatial modeling for COVID-19 analysis: An Indian case study

2020 ◽  
Vol 8 (S1) ◽  
pp. 19-32
Author(s):  
Iyyanki M ◽  
Prisilla J ◽  
Kandle S
Keyword(s):  
Spatial Distribution ◽  
Linear Regression ◽  
Spatial Data ◽  
Spatial Modeling ◽  
Spatial Models ◽  
Least Square ◽  
Weighted Regression ◽  
Ordinary Least Square ◽  
Geographical Weighted Regression

The coronavirus disease 2019 (COVID-19) outbreak in India from January 31, 2020, onwards to June 15, 2020, has reached confirmed cases over 3,32,424 that are being reported. The aim of this study is to predict and explore the spatial distribution of COVID-19 data of India using three models – geographical weighted regression (GWR), generalized linear regression (GLR), and ordinary least square (OLS). In this paper, the swift rise in COVID-19 cases is experiential after the lockdown period. This is explored using ArcGIS on the confirmed case of June 15, 2020, as the response with the explanatory of COVID-19 cases, i.e March 15, 2020, April 7, April 12, May 12, and June 1, 2020. The confirmed cases of the dataset is classified into three cases ie. case-1: June 15, 2020, vs March 15 and April 7, 2020; case-2: June 15, 2020 vs April 12, May 12 and June 1, 2020; and case-3: June 15, 2020 Vs all dates mentioned in discussion Hence, the prediction using GWR gave the much closer values for June 16, 2020. AICc of GWR (618.9038) was found to have the minimum value over GLR and OLS models. The day-wise increase and samples tested per day in twelve different states is analyzed using STATA. The number of testing varies with states to states, depending on the population and testing labs available. The percentage for each slope is achieved as m1 (-5.714 %), m2 (39.393%), m3 (6.521%) and m4 (46.938%). Keywords: COVID-19; GIS; spatial data; spatial models; testing samples

scholarly journals Estimating Urban Shared-Bike Trips with Location-Based Social Networking Data

2019 ◽  
Vol 11 (11) ◽  
pp. 3220 ◽  
Author(s):  
Fan Yang ◽  
Fan Ding ◽  
Xu Qu ◽  
Bin Ran
Keyword(s):  
Geographically Weighted Regression ◽  
Least Square ◽  
Weighted Regression ◽  
Transportation Mode ◽  
Ordinary Least Square ◽  
Social Network Data ◽  
Point Of Interest ◽  
The Relationship ◽  
Excessive Number

Dockless shared-bikes have become a new transportation mode in major urban cities in China. Excessive number of shared-bikes can occupy a significant amount of roadway surface and cause trouble for pedestrians and auto vehicle drivers. Understanding the trip pattern of shared-bikes is essential in estimating the reasonable size of shared-bike fleet. This paper proposed a methodology to estimate the shared-bike trip using location-based social network data and conducted a case study in Nanjing, China. The ordinary least square, geographically weighted regression (GWR) and semiparametric geographically weighted regression (SGWR) methods are used to establish the relationship among shared-bike trip, distance to the subway station and check ins in different categories of the point of interest (POI). This method could be applied to determine the reasonable number of shared-bikes to be launched in new places and economically benefit in shared-bike management.

PENGARUH KNOWLEDGE MANAGEMENT, KOMPETENSI, MOTIVASI TERHADAP KINERJA KARYAWAN

2015 ◽  
Vol 5 (2) ◽  
pp. 1
Author(s):  
Miftahol Arifin
Keyword(s):  
Knowledge Management ◽  
Linear Regression ◽  
Significant Influence ◽  
Employee Performance ◽  
Least Square Method ◽  
Least Square ◽  
Analysis Tool ◽  
Ordinary Least Square ◽  
Competence Motivation ◽  
Performance Analyze

The purpose of this research is to analyze the influence of knowledge management on employee performance, analyze the effect of competence on employee performance, analyze the influence of motivation on employee performance). In this study, samples taken are structural employees PT.centris Kingdom Taxi Yogyakarta. The analysis tool in this study using multiple linear regression with Ordinary Least Square method (OLS). The conclusion of this study showed that the variables of knowledge management has a significant influence on employee performance, competence variables have an influence on employee performance, motivation variables have an influence on employee performance, The analysis showed that the variables of knowledge management, competence, motivation on employee performance.Keywords: knowledge management, competence, motivation, employee performance.

Pengaruh pertumbuhan ekonomi, inflasi dan pengangguran terhadap tingkat kemiskinan di Sumatera Selatan

2019 ◽  
Vol 16 (1) ◽  
pp. 1-10
Author(s):  
Novegya Ratih Primandari
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Linear Regression ◽  
Linear Regression Model ◽  
Time Series Data ◽  
Secondary Data ◽  
Poverty Rate ◽  
Least Square ◽  
Series Data ◽  
Ordinary Least Square

This research aims to analyze effect of economic growth, inflation and Unemployment on the Rate of Poverty in the Province of South Sumatera. This research used secondary data in the form of time series data from 2001-2017. The method used quantitative approach by applying a linear regression model with OLS estimation Ordinary Least Square (OLS) method. The results of this study indicate that partially and simultaneously Economic Growth, Inflation and Unemployment have a significant effect on the Poverty Rate in the Province of South Sumatera.

Insurance regulations, risk and performance in Ghana

2019 ◽  
Vol 28 (1) ◽  
pp. 74-96
Author(s):  
Baah Aye Kusi ◽  
Abdul Latif Alhassan ◽  
Daniel Ofori-Sasu ◽  
Rockson Sai
Keyword(s):  
Random Effect ◽  
Least Square ◽  
Insurance Market ◽  
Content Type ◽  
Ordinary Least Square ◽  
Negative Effect ◽  
And Performance ◽  
First Time

Purpose This study aims to examine the hypothesis that the effect of insurer risks on profitability is conditional on regulation, using two main regulatory directives in the Ghanaian insurance market as a case study. Design/methodology/approach This study used the robust ordinary least square and random effect techniques in a panel data of 30 insurers from 2009 to 2015 to test the research hypothesis. Findings The results suggest that regulations on no credit premium and required capital have insignificant effects on profitability of insurers. On the contrary, this study documents evidence that both policies mitigate the effect of underwriting risk on profitability and suggests that regulations significantly mitigate the negative effect of underwriting risk to improve profitability. Practical implications The finding suggests that policymakers and regulators must continue to initiate, design and model regulations such that they help tame risk to improve the performance of insurers in Ghana. Originality/value This study provides first-time evidence on the role of regulations in controlling risks in a developing insurance market.

Penerbitan Maklumat Tiga Dimensi Sebuah Lukisan Garisan Menggunakan Kaedah Jumlah Kuasa Dua Terkecil

2012 ◽  
Author(s):  
Habibollah Haron ◽  
Dzulkifli Mohamed
Keyword(s):  
Linear System ◽  
Line Drawing ◽  
Least Square Method ◽  
Least Square ◽  
Geometric Information ◽  
Ordinary Least Square ◽  
Total Least Square ◽  
Regular Line ◽  
Space Image

Pengekstrakan lukisan garisan melibatkan proses menukar lukisan garisan tidak sekata kepada lukisan sekata, mendapatkan entiti asas simpang, garisan serta kawasan dan seterusnya mendapatkan maklumat tiga dimensi lukisan. Proses penukaran lukisan tidak sekata akan menghasilkan maklumat dua dimensi lukisan dan maklumat geometri dua dimensi lukisan iaitu simpang, garisan dan kawasan masing-masing yang mewakili unjuran bucu, pinggir dan permukaan dalam tiga dimensi. Berdasarkan maklumat geometri dua dimensi ini, jenis kenalaran imej ditentukan untuk membentuk set sistem linear lebih tentu. Grimstead menggunakan empat kenalaran imej dan menggunakan lelaran kuasa dua terkecil untuk menyelesaikan sistem linear lebih tentu yang dihasilkan. Kertas kerja ini akan mencadangkan kaedah jumlah kuasa dua terkecil untuk menyelesaikan sistem linear lebih tentu yang dibentuk oleh dua kenalaran imej. Perbandingan dengan kaedah Grimstead akan ditunjukkan dan penerangan akan dibantu oleh kes kajian dan paparan output. Kata kunci: Terjemahan garisan; Jumlah Kuasa Dua Terkecil; ruang gradien; kenalaran imej; sistem linear Line drawing interpretation involves process of converting irregular line drawing to regular line drawing. The converting process produces junctions, lines and regions that are two-dimensional projection of vertices, edges, and faces of a solid model respectively. Based on the geometric information obtained, image regularities are determined and a over-determined sets of linear systems is developed. Grimstead used the three image regularities in the linear system and iterative ordinary least square to solve them. The paper is intended to propose Total Least Square method in solving over-determined sets of linear system of image regularities of a line drawing. Two image regularities have been used. The solutions obtained are visualized with the help of MATLAB tool. Case study is given to assist the explaination. Key words: Line Interpretation; Total Least Square Method; Gradient Space; Image Regularities; Linear System

Isolation of Interacting Channels in Decentralized Control Systems Using Instrumental Variables Method

2014 ◽  
Vol 625 ◽  
pp. 435-438
Author(s):  
Mohamed Rahim ◽  
M. Ramasamy ◽  
Lemma Dendena Tufa ◽  
A. Faisal
Keyword(s):  
Control Systems ◽  
Instrumental Variables ◽  
Decentralized Control ◽  
Partial Correlation ◽  
Significant Contribution ◽  
Model Error ◽  
Least Square ◽  
Ordinary Least Square ◽  
Interaction Dynamics

This paper describes the use of partial correlation based instrumental variables method for the identification and isolation of weak interaction dynamics between subsystems in decentralized control systems. Unlike the available methods based on the ordinary least square, the proposed method clearly discriminates the interaction channels that have significant contribution to the interconnected subsystem from the ones which do not by reducing the model error that arises due to the process inputs correlation. The efficacy of the proposed method is illustrated through a case study.

scholarly journals Solving Multicollinearity Problem in Linear Regression Model: The Review Suggests New Idea of Partitioning and Extraction of the Explanatory Variables

2021 ◽  
Vol 2 (1) ◽  
pp. 12-20
Author(s):  
Kayode Ayinde, Olusegun O. Alabi ◽  
Ugochinyere Ihuoma Nwosu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Real Data ◽  
Least Square ◽  
Model Parameters ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Wide Range ◽  
High Level

Multicollinearity has remained a major problem in regression analysis and should be sustainably addressed. Problems associated with multicollinearity are worse when it occurs at high level among regressors. This review revealed that studies on the subject have focused on developing estimators regardless of effect of differences in levels of multicollinearity among regressors. Studies have considered single-estimator and combined-estimator approaches without sustainable solution to multicollinearity problems. The possible influence of partitioning the regressors according to multicollinearity levels and extracting from each group to develop estimators that will estimate the parameters of a linear regression model when multicollinearity occurs is a new econometrics idea and therefore requires attention. The results of new studies should be compared with existing methods namely principal components estimator, partial least squares estimator, ridge regression estimator and the ordinary least square estimators using wide range of criteria by ranking their performances at each level of multicollinearity parameter and sample size. Based on a recent clue in literature, it is possible to develop innovative estimator that will sustainably solve the problem of multicollinearity through partitioning and extraction of explanatory variables approaches and identify situations where the innovative estimator will produce most efficient result of the model parameters. The new estimator should be applied to real data and popularized for use.

scholarly journals PENGARUH KOMPETENSI DAN KOMPENSASI TERHADAP KINERJA KARYAWAN

2020 ◽  
Vol 3 (1) ◽  
pp. 58-67
Author(s):  
Yadi Maryadi ◽  
Yulia Misrania
Keyword(s):  
Regression Coefficient ◽  
Employee Performance ◽  
Regression Equation ◽  
Least Square ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Hotel Employees ◽  
Independent Variable ◽  
The City

This study aims to determine the effect of Competence and Compensation on Employee Performance (Case Study on Hotel Employees in the city of Pagar Alam). By using primary data and secondary data, this research uses the Ordinary Least Square method. The results of this study are the findings of the influence of Compensation and Compensation on Employee Performance (Case Study on Hotel Employees in the City of Pagar Alam) can be explained as follows. Based on the Regression analysis in the table above, the constant value α = 38,868 and coefficient b1 =. 083 and b2 = .396, so that the multiple linear regression equation is: Y = 38.868+ 0.083X1 + 0.396X2. The regression equation that has been obtained can be used to predict the value of the independent variable and the dependent variable, as follows: A constant value of 38,868 means that if all independent variables are zero, then the performance of hotel clerks in the city of Pagar Alam is valued at 38,868. Competence (X1) has a regression coefficient of .083 meaning that each increase in Competency by 1 unit then the performance of hotel employees increases by .083 assuming the other factors remain. Compensation (X2) has a regression coefficient of .396 meaning that each increase in compensation is 1 unit, the performance of hotel employees increases by .396. From the determination coefficient table above, it can be seen that the R Square figure is 0.931. This means that the influence between the independent variables with the dependent variable is 93.1% while the remaining 6.9% is influenced by other factors outside the regression model analyzed. From these figures it can be concluded that the influence of the independent variable with the dependent variable is very strong.   Penelitian ini bertujuan untuk mengetahui pengaruh Kompetensi dan Kompensasi terhadap Kinerja Karyawan (Studi Kasus pada Karyawan hotel di Kota Pagar Alam). Dengan menggunakan data primer dan data skunder penelitian ini menggunakan metode Regresi Linear Sederhana (Ordinary Least Square). Adapun hasil Penelitian ini adalah Hasil temuan mengenai pengaruh Komptensi dan Kompensasi terhadap Kinerja Karyawan (Studi Kasus pada Karyawan hotel di Kota Pagar Alam) dapat dijelaskan sebagai berikut. Berdasarkan analisis Regresi pada tabel diatas didapatkan  nilai konstanta α = 38.868 dan koefisien b1 = . 083  dan b2 = .396, sehingga persamaan regresi linier berganda adalah :  Y =  38.868+ 0.083X1 + 0.396X2. Persamaan regresi yang telah diperoleh dapat dipergunakan untuk memprediksi nilai variabel independen dan variabel dependen yaitu sebagai berikut : Nilai konstanta sebesar 38.868 artinya bahwa jika semua variabel independen benilai nol, maka kinerja kayawan hotel di kota Pagar Alam bernilai sebesar 38.868. Kompetensi (X1) mempunyai koefisien regresi sebesar .083 artinya setiap kenaikan Kompetensi sebesar 1 satuan maka kinerja karyawan hotel naik sebesar .083 dengan asumsi faktor-faktor yang lain tetap. Kompensasi (X2) mempunyai koefisien regresi sebesar .396 artinya setiap kenaikan kompensasi sebesar 1 satuan maka kinerja karyawan hotel naik sebesar .396. Dari tabel koefisien determinasi di atas, dapat dilihat bahwa angka R Square sebesar 0.931. Hal ini berarti pengaruh antar variabel independen dengan variabel dependen sebesar 93,1% sedangkan sisanya sebesar 6,9% dipengaruhi oleh faktor-faktor lain di luar model regresi yang dianalisis. Dari angka tersebut dapat diambil kesimpulan bahwa pengaruh antara variabel independen dengan variabel dependen sangat kuat.

scholarly journals DUKUNGAN PEMERINTAH DAERAH, OPTIMALISASI ASSET DAN PROFESIONALISME UNTUK MENINGKATKAN PENDAPATAN ASLI DAERAH (PAD)

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Komang Adi Kurniawan Saputra ◽  
A.A Ketut Jayawarsa ◽  
Putu Budi Anggiriawan
Keyword(s):  
Local Government ◽  
Linear Regression ◽  
Asset Management ◽  
Sampling Technique ◽  
Least Square ◽  
Government Support ◽  
Theoretical Research ◽  
Ordinary Least Square ◽  
Factors Influencing ◽  
The Village

The aim of this research is to examine the factors influencing the original income level of the villages by taking the research location in the villages managing the village fund in Buleleng-Bali Regency. Total number of 129 villages. The number of samples used in this study is equal to the number of population, The sampling technique in this study was total sampling. Meanwhile, to test the hypothesis using multiple linear regression with OLS model (Ordinary Least Square). The results obtained in this study indicate that Local Government Support, Optimalization of Village Asset Utilization and Professionalism of Village Asset Management have a significant effect on original income of the village. The contribution of this theoretical research is to contribute theoretical enrichment that underlies the increase of village original income and its practical contribution, this research can be one of reference for village apparatus, village counselor, and local government in making policy related to asset management or village property

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