A physics-based parametric regression approach for feedwater pump system diagnosis

2022 ◽  
Vol 166 ◽  
pp. 108692
Author(s):  
Tat Nghia Nguyen ◽  
Roberto Ponciroli ◽  
Timothy Kibler ◽  
Marc Anderson ◽  
Molly J. Strasser ◽  
...  
Keyword(s):  
Pump System ◽  
Parametric Regression ◽  
System Diagnosis ◽  
Feedwater Pump ◽  
Regression Approach

Truncated Spline Estimation of Percentage Poverty Modeling in Papua Province

2021 ◽  
pp. 69-82
Author(s):  
Ni Putu Ayu Mirah Mariati ◽  
Nyoman Budiantara ◽  
Vita Ratnasari
Keyword(s):  
Nonparametric Regression ◽  
Semiparametric Regression ◽  
Poor People ◽  
Regression Curve ◽  
Parametric Regression ◽  
Regression Approach ◽  
Spline Estimation ◽  
High Flexibility

In estimating the regression curve there are three approaches, namely parametric regression, nonparametric regression and semiparametric regression. Nonparametric regression approach has high flexibility. Nonparametric regression approach that is quite popular is Truncated Spline. Truncated Spline is a polynomial pieces which have segmented and continuous. One of the advantages of Spline is that it can handle data that changes at certain sub intervals, so this model tends to search for data estimates wherever the data pattern moves and there are points of knots. In reality, data patterns often change at certain sub intervals, one of which is data on poverty in the Papua Province. Papua Province is ranked first in the percentage of poor people in Indonesia. The best of model Truncated Spline in nonparametric regression for the poverty model in Papua Province is using a combination of knot.  

scholarly journals Analyzing The Effect of BI 7-Days Repo Rate on The Jakarta Composite Index Using Nonparametric Regression Approaches Based on Least Square Spline Estimator

2021 ◽  
Vol 17 (3) ◽  
pp. 447-461
Author(s):  
Christopher Andreas ◽  
Feevrinna Yohannes Harianto ◽  
Elfhira Juli Safitri ◽  
Nur Chamidah
Keyword(s):  
Nonparametric Regression ◽  
Composite Index ◽  
Negative Relationship ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Absolute Deviation ◽  
Parametric Regression ◽  
Regression Approach ◽  
Repo Rate

During the Covid-19 pandemic, the Indonesia stock market was under great pressure, so that the value of the Jakarta Composite Index (JCI) fluctuated greatly. To maintain economic stability, Bank Indonesia has regulated monetary policy such as setting the BI 7-Days Repo Rate. Analysis of this effect is important to formulate the right policy. This study aims to design the best model in describing the relationship between JCI value and BI 7-Days Repo Rate. The analysis was carried out by using parametric regression approach based on the ordinary least square method and nonparametric regression approach based on least square spline estimator. The results showed that the parametric regression models failed to meet the classical assumptions. Meanwhile, nonparametric regression can produce an optimal model with high accurate prediction, with an overall mean absolute percentage error value of 3.16%. Furthermore, mean square error, coefficient of determination, and mean absolute deviation also show good results. Thus, the effect of the BI 7-Days Repo Rate on the JCI value forms a quadratic pattern, in which a positive relationship is formed when the BI 7-Days Repo Rate is set at more than 4.25% and vice versa for a negative relationship.

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