Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

Prahutama, Alan; Suparti,; Utami, Tiani Wahyu

doi:10.1088/1742-6596/974/1/012067

Cited by 11 publications

(6 citation statements)

References 3 publications

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“…In nonparametric regression model with the Fourier series approach, parameter hypothesis testing has not been carried out previously. Referring to previous researches, this model was used by several researchers for modelling or even for prediction in various fields/data [see, 12 , [15] , [16] , [17] ]. However, these researches were only focused on estimation and modelling.…”

Section: Parameter Hypothesis Testing Using the Lrt Methodsmentioning

confidence: 99%

“…However, if the regression curve of

is assumed to be only an unknown function and presented as a linear model as of (7) , then we could use the Ordinary Least Square (OLS) method that minimizes the sum of the square of the error. By using the optimization of the OLS method, the parameter estimation of

could be obtained as follows [ 12 , [15] , [16] , [17] ].

where

…”

Section: The Model and Its Estimationmentioning

confidence: 99%

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A method for parameter hypothesis testing in nonparametric regression with Fourier series approach

Ramli,

Budiantara,

Ratnasari

2023

MethodsX

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Section: Parameter Hypothesis Testing Using the Lrt Methodsmentioning

confidence: 99%

“…However, if the regression curve of

could be obtained as follows [ 12 , [15] , [16] , [17] ].

where

…”

Section: The Model and Its Estimationmentioning

confidence: 99%

A method for parameter hypothesis testing in nonparametric regression with Fourier series approach

Ramli,

Budiantara,

Ratnasari

2023

MethodsX

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“…Knot points are joint fusion points that have behavior changes in the data. One appropriate method for selecting the optimal knot points is Generalized Cross-Validation (GCV) [19]. It is said to be the optimal knot point when obtained the lowest or minimum GCV value.…”

Section: Data and Data Processingmentioning

confidence: 99%

Spline Nonparametric Regression to Analyze Factors Affecting Gender Empowerment Measure (GEM) in East Java

Mahfiroh

Farida

2021

CAUCHY

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Gender is a multidimensional issue that's not limited to gender discrimination, but alsoincludes the economic, educational, and health aspects, which then become the focus of almost all the Sustainable Development Goals (SDGs). Evaluation of the development devoted to the perspective of the gender using several indicators, Gender Development Index (GDI) and Gender Empowerment Measure (GEM). GEM describes the role of women in the economic sphere and is measured by equality in political participation. GEM of East Java for 5 consecutive years (2014 – 2018) is lower than the average national GEM. This study aims to identify factors affecting GEM in East Java using nonparametric regression spline quadratic. The result ofthe regression model shows the factors affecting GEM East Java is the Labor Force Participation Rate(LFPR) population of women (), School Participation Rate(SPR) high school population of women (), Percentage of Population Female thatWorking in the formal sector (), sex ratio (), Percentage of Population Female that Working as members of People’s Representative Council (), Percentage of Population Female that working as Civil Servants (), and rate of women's income donations (). The model generates value of 93.74% and MAPE of 3.22%.This research contributes to the implementation of non-parametric spline regression in identifying various factors that influence social phenomena.

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“…Regression analysis is an analysis to determine the effect between the dependent variable and the independent variable. If you want to find a pattern of relationship between the independent variable and the dependent variable (y), where the shape of the regression curve is unknown, the method used is a nonparametric regression approach [13]. The function 𝑓(𝑡 𝑖 ) is a regression curve of unknown shape.…”

Section: Introductionmentioning

confidence: 99%

Statistical Downscaling Using Regression Nonparametric of Fourier Series-Polynomial Local of Climate Change

Utami,

Fauzi,

Yuliyanto

2023

BAREKENG: J. Math. & App.

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Indonesia is a tropical country that is vulnerable to the impacts of climate change. Climate change causes an effect on the level of comfort (heat stress) that can affect the level of human immunity, one of the indices to calculate the level of human comfort (heat stress) is the Thermal Humidity Index (THI). Climate change scenarios modeled in Earth System Models (ESMs). ESM has a coarse resolution and is subject to considerable bias. This research is using secondary data. The data source used in this study comes from the Coupled Model Intercomparison Project (CMIP5). This research will focus on projected heat stress which is calculated based on THI with the temperature and humidity variables. Therefore, in this research to reduce the bias correction method used Statistical Downscaling (SD) and nonparametric regression. The results of the bias correction using the Statistical Downscaling (SD) method and Nonparametric Regression Fourier-Polynomial Local Series in this study the R-square value for Relative Humidity yields 95% and for Temperature yields 94%. The projection of climate change based on the value of the Temperature Humidity Index (THI) in Indonesia in the category of 50% of the population of Indonesians feeling comfortable conditions occurred in 2006-2059. Then the population of citizens in Indonesia felt uncomfortable conditions occurred in 2060 to 2100 with a THI value of 27.0730°C - 27.7800°C.

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Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

Cited by 11 publications

References 3 publications

A method for parameter hypothesis testing in nonparametric regression with Fourier series approach

A method for parameter hypothesis testing in nonparametric regression with Fourier series approach

Spline Nonparametric Regression to Analyze Factors Affecting Gender Empowerment Measure (GEM) in East Java

Statistical Downscaling Using Regression Nonparametric of Fourier Series-Polynomial Local of Climate Change

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