scholarly journals Modeling Continuous Non-Linear Data with Lagged Fractional Polynomial Regression

2018 ◽  
Vol 6 (5) ◽  
Author(s):  
Kazeem Kehinde Adesanya ◽  
Abass Ishola Taiwo ◽  
Adebayo Funmi Adedodun ◽  
Timothy Olabisi Olatayo
Keyword(s):  
Coefficient Of Variation ◽  
Polynomial Regression ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Fractional Polynomial ◽  
Non Linear ◽  
Unit Increase ◽  
Independent Variable ◽  
The Relationship ◽  
Better Than

Fractional Polynomial regression is a form of regression analysis in which the relationship between the independent variable and the dependent variable is modelled as a 1/nth degree polynomial. Thus, this work is used to propose an extension of Fractional Polynomial Regression (FPR) term Lagged Fractional Polynomial Regression (LFPR) which is an alternative method to traditional techniques of analysing the pattern and degree of relationship between two or more continuous non-linear data. The coefficients of the proposed method were estimate using Maximum Likelihood Estimation method. From the results, the LFPR model indicated that for a unit increase in Evaporation, Humidity and Temperature there will be an increase in the millimeter of rainfall series on yearly basis. The value of coefficient of variation (R2) for the LFPR and FPR were 99% and 77%. While the value of adjusted Coefficient of Variation (R2) for LFPR and FPR were 96% and 75% respectively. Hence, the proposed method outperformed and adequately explained the variation in the dependent variable better than Fractional Polynomial Regression based on the values (R2) and adjusted (R2).

The use of faecal nitrogen as an index for estimating the consumption of herbage by grazing animals

1963 ◽  
Vol 61 (1) ◽  
pp. 33-43 ◽  
Author(s):  
G. W. Arnold ◽  
M. L. Dudzinski
Keyword(s):  
Organic Matter ◽  
Nitrogen Concentration ◽  
Linear Equations ◽  
Slope Position ◽  
Seasonal Differences ◽  
Faecal Nitrogen ◽  
Independent Variable ◽  
Regression Relations ◽  
The Relationship ◽  
Better Than

Data from thirty-five digestibility trials with sheep in metabolism cages were used to investigate statistically the relationships between organic matter intake (I), faecal organic matter output (F), and the nitrogen concentration in faecal organic matter (N).The data fell easily into groups due to botanical or seasonal differences in the feed. These groups of data were homogeneous and provided highly significant linear equations of the forms I = bF + cFN and I = a + cFN. When compared these groups of data sometimes showed differences in slope, position or both. A quadratic expressionI = bF + cFN + dFN2was found to accommodate a majority of the data but to be less precise than I = a + cFN.A further expression incorporating N as an independent variable was also examined,I = a + cFN2 + eN.This expression, although far from being universally adequate, proved to be generally better than existing formulae. When applied to the data of Greenhalgh et. al. (1960), it substantially reduced heterogeneity between data for spring and data for summer pastures.Causes of variation in the relationship between organic-matter intake and nitrogen in faeces, and some of the hazards of extrapolation from empirical regression relations, are discussed.

The relationship between nitrogen supply and the nitrogen yield of cut grass swards

1977 ◽  
Vol 88 (2) ◽  
pp. 289-292 ◽  
Author(s):  
I. R. Richards ◽  
R. D. Hobson
Keyword(s):  
Nitrogen Supply ◽  
Linear Functions ◽  
Available Nitrogen ◽  
England And Wales ◽  
Nitrogen Yield ◽  
Non Linear ◽  
Using Data ◽  
The Relationship ◽  
Potential Maximum ◽  
Better Than

SUMMARYUsing data from 140 experiments conducted at sites throughout England and Wales, a relationship between nitrogen supply and the nitrogen yield of cut grass swards was sought. One linear and three non-linear functions were fitted to the data. The non-linear functions fitted the data slightly better than did the linear and, over the range in nitrogen supply normally found, provided consistent predictions of grass nitrogen yield. The recovery of available nitrogen in the herbage was found to decline with level of nitrogen supply from a potential maximum of 79%.

scholarly journals Empirical Analysis in the Relationship Between the Consumption and Economic Growth Based on the Structural Equation Model

2016 ◽  
Vol 4 (5) ◽  
pp. 419-427
Author(s):  
Erxin Zhang ◽  
Wancai Yang
Keyword(s):  
Economic Growth ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Equation Model ◽  
Positive Effects ◽  
Structure Equation Model ◽  
The Relationship ◽  
Maximum Likelihood Estimation Method

AbstractThis paper constructs the relationship between consumption and economic growth by a structure equation model and uses the provincial panel data of 29 provinces (municipalities, autonomous regions) from 1992 to 2010 in China, using maximum likelihood estimation method to analyze empirically the relationship between the consumption and economic growth in China. The result shows that the path coefficients between consumptions and economic growth are all positive, that suggests the consumption has significant positive effects on the economic growth. Also in this paper, it gives a new try to use a structural equation model to research the relationship between consumption and economic growth.

scholarly journals PEMODELAN TINGKAT KERAWANAN DEMAM BERDARAH DI KABUPATEN BANJAR DENGAN METODE ANALISIS REGRESI LOGISTIK YANG TERBOBOTI GEOGRAFIS

2019 ◽  
Vol 14 (4) ◽  
pp. 2393
Author(s):  
Dewi Sri Susanti ◽  
Pamona Dwi Rahayu ◽  
Oni Soesanto
Keyword(s):  
Logistic Regression ◽  
Dengue Fever ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Rate Model ◽  
Independent Variables ◽  
Dependent Variables ◽  
Geographically Weighted Logistic Regression ◽  
The Relationship ◽  
Maximum Likelihood Estimation Method

Regression analysis is a metodh for investigating the relationship between the dependent variable (Y) and independent variables (X). Logistic regression is a regression model that used related to the qualitative Dependent variable. If the Logistic regression influenced by factors of the location of each point from observation where the data is collected, it will be a Geographically Weighted Logistic Regression (GWLR). In the case of insecurity rate model of dengue fever has two or more categories, so that this case can be resolved by GWLR. This research aims to clarify the procedure of testing the parameters GWLR model and form insecurity rate model of dengue fever with GWLR method in Banjar Regency. Dependent variable with catagoric is Insecurity rate of dengue fever ( ) and independent variables is the population density ( ), the distance from the capital of the subdistrict to capital of regency ( ), fogging per subdistrict ( ), the percentage of households living clean and healthy ( ), pesentase healthy homes ( ), the percentage of access to decent sanitation ( ). The results from this research are estimate parameters using Maximum Likelihood Estimation method and presented in the form of thematic map that shows not all dependent variables give influence on Insecurity rate dengue fever

scholarly journals Investigating the Relationship between Marketing Knowledge Sharing and Developing Competitive Advantage (Case Study: Arak Shazand Petrochemical)

2016 ◽  
Vol 11 (2) ◽  
pp. 8
Author(s):  
Mohamad Reza Hamidizadeh ◽  
Parinaz Aghaei Meibodi
Keyword(s):  
Competitive Advantage ◽  
Knowledge Sharing ◽  
Hypothesis Test ◽  
University Professors ◽  
Confirmatory Factor ◽  
Unit Increase ◽  
Independent Variable ◽  
Spss Software ◽  
The Relationship

The aim of this study is to investigate the relationship between marketing knowledge sharing and developing competitive advantage. This research is an applied objective research and data collection method of description-correlation nature the subjects under study by this research are employees of Arak Shazand petrochemical industry. The sample size was estimated 90 people. The method is stratified random sampling. A standard questionnaire was used to collect data. Marketing knowledge sharing questionnaire of Moghimi and Ramazani (2011) contains 17 items and developing competitive advantage questionnaire of Hill and Jones (2010) contains 16 items. Logical validity (face and content) of questionnaires was reviewed and approved through several university professors and several experts of this industry. Also, construct validity was reviewed and approved by confirmatory factor analysis using AMOS software. Cronbach's alpha coefficient of 0.7 was obtained for variables that indicate internal consistency of items and acceptable reliability of the questionnaire. The research hypothesis test using univariate linear regression was performed with application of SPSS software. The results showed that, given that the t-statistic value is greater than 1.96 (t = 6.48), the relationship between two variables, competitive advantage and marketing knowledge sharing was significant at the 5% error level  Standard regression coefficient (0.57) also specified the share of independent variable in explaining the changes of dependent variable so that for every one unit increase in variable of marketing knowledge sharing, competitive advantage increases 0.57.

scholarly journals Is the relationship between corruption and domestic investment non-linear in Nigeria? Empirical evidence from quarterly data

2021 ◽  
Vol 39 (3) ◽  
Author(s):  
Nurudeen Abu ◽  
Mohd Zaini Abd Karim
Keyword(s):  
Empirical Evidence ◽  
Inflation Rate ◽  
Estimation Method ◽  
Oil Prices ◽  
Domestic Investment ◽  
Quarterly Data ◽  
Estimation Techniques ◽  
Non Linear ◽  
Corruption Index ◽  
The Relationship

This study employs the ARDL estimation method to investigate whether corruption and domestic investment relationship is non-linear in Nigeria using quarterly data over the 1996-2019 period. Other alternative estimation techniques such as the CCR, DOLS and FMOLS were used to check for consistency of the results. The results demonstrate that corruption-domestic relationship is non-linear. Although domestic investment reduces with an improvement in the corruption index (reducing corruption), a further reduction in corruption raises the domestic investment. Other significant determinants of domestic investment include income level, oil prices and inflation rate. Based on these outcomes, this study recommends policies to reduce corruption to raise domestic investment.

scholarly journals ANALISA ALGORITMA DAN KARAKTERISTIK KECEPATAN KENDARAAN DI RUAS JALAN ARTERI KOTA SURABAYA

2019 ◽  
Vol 15 (2) ◽  
pp. 122-135
Author(s):  
Afifah Ajeng ◽  
Vicky Agustin ◽  
Hendrata Wibisana
Keyword(s):  
Polynomial Regression ◽  
Polynomial Model ◽  
Measurement Time ◽  
Vehicle Speed ◽  
The Road ◽  
Road Section ◽  
Independent Variable ◽  
On The Road ◽  
The Relationship ◽  
Calculated Model

Vehicle speed is one of the parameters used to detect the characteristics of traffic on a road segment. Vehicle speed is a variable that determines the level of road service as well as the value of the comparison between traffic flow and vehicle density on the road section under study. This study aims to develop an appropriate algorithm that can describe the situation on the arterial road Ir. H. Soekarno about the speed of vehicles passing in it. The method used in this study is polynomial regression with vehicle speed as a dependent variable and the measurement time as a independent variable. The model is said to be good and can be represented by looking at the correlation value R2 that is in each calculated model. The results obtained from this study are that the relationship between vehicle speed and measurement time has the best results on the polynomial model level 7 for measurements in the morning and evening with the same polynomial model. This shows that the graph of the velocity of time is not linear but is a polynomial function. From this research, it can be concluded that the Ir.H.Soekarno road section has varied vehicle speed characteristics and the appropriate mathematical model algorithm is the 6th polynomial model with R2 correlation value of 0.88

scholarly journals Odd Lindley-Lomax Model: Statistical Properties and Applications

1970 ◽  
pp. 419-430
Author(s):  
M. Masoom Ali ◽  
Mustafa Ç. Korkmaz ◽  
Haitham M. Yousof ◽  
Nadeem Shafique Butt
Keyword(s):  
Maximum Likelihood ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Good Alternative ◽  
Model Parameters ◽  
Lifetime Data ◽  
Monte Carlo Simulation Study ◽  
Computational Aspects ◽  
Maximum Likelihood Estimation Method ◽  
Better Than

 In this work, we focus on some new theoretical and computational aspects of the Odd Lindley-Lomax model. The maximum likelihood estimation method is used to estimate the model parameters. We show empirically the importance and flexibility of the new model in modeling two types of aircraft windshield lifetime data. This model is much better than exponentiated Lomax, gamma Lomax, beta Lomax and Lomax models so the Odd Lindley-Lomax lifetime model is a good alternative to these models in modeling aircraft windshield data. A Monte Carlo simulation study is used to assess the performance of the maximum likelihood estimators. 

scholarly journals Estimation of VECM Parameter Using Bayesian Approach: An Application to Analysis of Macroeconomic Variables

2020 ◽  
Vol 9 (6) ◽  
pp. 113
Author(s):  
Meilina Retno Hapsari ◽  
Suci Astutik ◽  
Loekito Adi Soehono
Keyword(s):  
Parameter Estimation ◽  
Exchange Rate ◽  
Interest Rates ◽  
Money Supply ◽  
Bayesian Approach ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Macroeconomic Variables ◽  
Us Dollar ◽  
The Relationship

This study uses Bayesian approach to estimate Vector Error Correction Model (VECM). The aims of this study is to analyze the relationship between macroeconomic variables in Indonesia. To analyze the best method to influence government targets or policies on economic growth by studying the relationships of many macroeconomic variables. Previous studies in analyzing the relationship between macroeconomic variables with VECM analysis, using the Maximum Likelihood Estimation. However this estimation method cannot solve the problem of overparameterization in VECM model. The variables used in this study are six macroeconomic variables in Indonesia in 2010 quarter 1 to 2019 quarter 4 are GDP, the money supply, exchange rate of rupiah to US dollar, exports, imports and interest rates. The number of data in this study is less than the number of estimated parameters causing overparameterization problems. Therefore, this study uses the Bayesian parameter estimation method to avoid overparameterization problems in economic data. The model obtained from this study is the BVECM(3) and it has been proven that the model is suitable (the model diagnostic test). Based on the parameter estimation results of BVECM(3), the significant variables affecting GDP are GDP itself, the money supply, exchange rate of rupiah to US Dollar, exports, imports and the interest rate for Bank Indonesia Certificates. In addition, there is a two-way relationship that affects each other, namely the relationship between GDP and the money supply, exports and imports, exports and interest rates, and between imports and interest rates.

scholarly journals Functional SAC model: With application to spatial econometrics

2021 ◽  
Vol 55 (1) ◽  
pp. 1-13
Author(s):  
Alassane Aw ◽  
Emmanuel N. Cabral
Keyword(s):  
Maximum Likelihood ◽  
Spatial Econometrics ◽  
Spatial Data ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Explanatory Variables ◽  
Dependent Variables ◽  
Spatial Autoregressive ◽  
The Relationship ◽  
Maximum Likelihood Estimation Method

Spatial autoregressive combined (SAC) models have been widely studied in the literature for the analysis of spatial data in various areas such as geography, economics, demography, regional sciences. This is a linear model with scalar response and scalar explanatory variables which allows for spatial interactions in the dependent variables and the disturbances. In this work we extend this modeling approach from scalar to functional covariate. The parameters of the model are estimated via the maximum likelihood estimation method. A simulation study is conducted to evaluate the performance of the proposed methodology. As an illustration, the model is used to establish the relationship between unemployment and illiteracy in Senegal.

Sign in / Sign up

Export Citation Format

Share Document