The Curve Estimation of Combined Truncated Spline and Fourier Series Estimators for Multiresponse Nonparametric Regression

Nurcahayani, Helida; Budiantara, I Nyoman; Zain, Ismaini

doi:10.3390/math9101141

Cited by 8 publications

(4 citation statements)

References 31 publications

(51 reference statements)

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“…The best model is a model with a minimum MSE, which means that the presumptive value of the model is close to the actual value. The MSE formula can be written as follows (Nurcahayani et al, 2021).…”

Section: Mean Square Error (Mse)mentioning

confidence: 99%

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Nonparametric Smoothing Spline Approach in Examining Investor Interest Factors

Pratama,

Fernandes,

Wardhani

et al. 2024

JTAM

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The nonparametric approach is an appropriate approach for patterns of relationships between predictor variables and response variables that are not or have not been known in form. In other words, there is no complete information about the pattern of relationships between variables. Curve estimation is determined based on relationship patterns in existing data. The nonparametric approach has great flexibility for estimating regression curves. This study aims to form a model on investor interest factors in improving tourism investment decisions with a nonparametric approach. The nonparametric method used is the smoothing spline regression method. The smoothing spline method is used because the modeling results from the smoothing spline approach can follow the relationship model between variables contained in the data. Thus, this method really helps researchers to model relationships between variables that are not linear and whose linear form is unknown. The results of the analysis showed that the nonparametric smoothing spline regression analysis method could model data by 94.63%, indicates that data variance can be explained by 94.63% with models, while other variance outside the study explain the remaining 5.37%. That is, investment motivation is one of the most important factors to improve investment decisions.

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Section: Mean Square Error (Mse)mentioning

confidence: 99%

“…Regression analysis assumes that the relationship between predictor variables and response variables can be explained through a known function and that function is a linear. If this assumption is violated, estimating parametric path functions cannot be done (Nurcahayani et al, 2021).…”

mentioning

confidence: 99%

Nonparametric Smoothing Spline Approach in Examining Investor Interest Factors

Pratama,

Fernandes,

Wardhani

et al. 2024

JTAM

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“…Many studies of spline estimators on nonparametric regression models have been carried out such as [25][26][27][28][29]. The nonparametric regression model which states the relationship between the predictor variable and the response variable can be written as follows;…”

Section: Spline Nonparametric Regressionmentioning

confidence: 99%

Spline Model in The Case of Cervical Cancer Patient Resilience

Hidayat

Ilyas²,

Yuliani³

2023

Trends Sci

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Cervical cancer ranks highest in developing countries, and ranks 10th in developed countries as a cause of death for women. In Indonesia, cervical cancer ranks second out of the 10 most common cancers based on Anatomical Pathology data in 2010 with an incidence rate of 20 %. The number of new women with cervical cancer ranges from 90 - 100 cases per 100,000 population and every year there are 40 thousand cases of cervical cancer. Cervical cancer is a gynecological disease that has a high level of malignancy and is caused by the Human Papilloma Virus (HPV). One method that can be used in the analysis of human survival is survival analysis using the Cox proportional hazard model. This research will use the development of the Cox model using the Spline function as its basis. Based on the results obtained, the developed model can model the data well and give a low MSE. Based on the developed model, it is found that the variables that influence the survival rate of cervical cancer patients are age, stage, type of PRC transfusion treatment and comorbidities. HIGHLIGHTS Due to in silico study such as molecular docking, molecular dynamic simulation is an important computational method for drug design. It can be used to predict the binding orientation of small molecule drug candidates to their protein targets. In addition, docking is also can be applied to predict small molecule affinity and activity. Thus, molecular docking has an important role in drug discovery and rational design The ligand interaction with the receptor was more stable due to the decreased binding free energy value The lowest binding free energy and lowest RMSD value of this molecule, which may presumably cause compound 3 to has better binding affinity compare to other compounds GRAPHICAL ABSTRACT

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“…Regression analysis is a statistical method that is commonly used in analyzing and explaining the relationship between variables, namely the response variable and the predictor variable [1], [2]. There are three types of approaches used to estimate the regression curve, namely parametric, nonparametric, and semiparametric regression [3].…”

Section: Introductionmentioning

confidence: 99%

Modeling Open Unemployment Rate in Kalimantan Island Using Nonparametric Regression With Fourier Series Estimator

Rahmania,

Sifriyani,

Dani

2024

BAREKENG: J. Math. & App.

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Nonparametric regression is a regression approach that is used to determine the relationship between the response variable and the predictor variable if the shape of the regression curve is unknown. One of the popular estimators used in nonparametric regression is the Fourier series estimator. Fourier series nonparametric regression is generally used when the pattern of the investigated data is unknown and there is a tendency for the pattern to repeat. The purpose of this study is to estimate nonparametric regression using the Fourier series approach and to find out the factors that influence the open unemployment rate on the island of Borneo in 2021. The criteria for the goodness of the model used Generalized Cross Validation (GCV) and the coefficient of determination ( ). Based on the results, it was found that the best nonparametric regression model for the Fourier series was the model with 5 oscillations which indicated a minimum GCV of 10.47 and an of 74.22%. Furthermore, based on the results of parameter significance testing either simultaneously or partially, it shows that all predictor variables have a significant effect on the open unemployment rate. The predictor variables include the labor force participation rate, the average length of schooling, the percentage of poor people, economic growth rate, and total population.

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The Curve Estimation of Combined Truncated Spline and Fourier Series Estimators for Multiresponse Nonparametric Regression

Cited by 8 publications

References 31 publications

Nonparametric Smoothing Spline Approach in Examining Investor Interest Factors

Nonparametric Smoothing Spline Approach in Examining Investor Interest Factors

Spline Model in The Case of Cervical Cancer Patient Resilience

Modeling Open Unemployment Rate in Kalimantan Island Using Nonparametric Regression With Fourier Series Estimator

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