FORECASTING OF THE AMOUNT OF RUPIAH BANKNOTES FLOWS IN THE EAST REGION OF INDONESIA USING CIRCULAR REGRESSION

Money is a tool that can be used in exchanging goods and services in a certain area. Increasing and decreasing in the money supply excessively can have a negative impact on the economy. For this reason, in order to maintain financial system stability in Indonesia, it is necessary to conduct an analysis of the data on the amount of outflows of rupiah currency at each Bank Indonesia office. In this study, a relationship analysis will be carried out between the eastern region of Indonesia and the amount of outflows of Bank Indonesia banknotes during the 2016-2018 period using circular regression analysis. The results showed that 83.03% of the variation in the amount of outflows of BI banknotes could be explained by the circular regression model that was formed. In addition, in the process of forecasting data on the amount of outflows of BI banknotes in the eastern region of Indonesia for the 2019-2020 period, the time series forecasting method is used which is based on the use of analysis of the relationship pattern between the estimated variables and the time variable.

Agenda Control and Timing of Bill Initiation: A Temporal Perspective on Coalition Governance in Parliamentary Democracies

Although democratic governance imposes temporal constraints, the timing of government policy making activities such as bill initiation is still poorly understood. This holds especially under coalition governments, in which government bills need to find approval by a partner party in parliament. We propose a dynamic temporal perspective in which ministers do not know whether they face a cooperative or competitive partner at the beginning of a term, but they learn this over time and use their agenda control to time further bill initiation in response. A circular regression analysis using data on more than 25,000 government bills from 11 parliamentary democracies over 30 years supports this temporal perspective, showing that ministers initiate bills later in the term when their previous bills have experienced greater scrutiny. Ministers further delay bill initiation when coalition parties’ incentives to deviate from compromise increase and when they have less power to constrain their bills’ scrutiny.

Comparative Study of Clustering-Based Outliers Detection Methods in Circular-Circular Regression Model

This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. Three measures of similarity based on the circular distance were used to obtain a cluster tree using the agglomerative hierarchical methods. A stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height was used as the cutoff point and classifier to the cluster group that exceeded the stopping rule as potential outliers. The performances of the algorithms have been demonstrated using the simulation studies that consider several outlier scenarios with a certain degree of contamination. Application to real data using wind data and a simulated data set are given for illustrative purposes. Thus, it has been found that Satari’s algorithm (S-SL algorithm) performs well for any values of sample size n and error concentration parameter. The algorithms are good in identifying outliers which are not limited to one or few outliers only, but the presence of multiple outliers at one time.

On the least trimmed squares estimators for JS circular regression model

The least trimmed squares (LTS) estimation has been successfully used in the robust linear regression models. This article extends the LTS estimation to the Jammalamadaka and Sarma (JS) circular regression model. The robustness of the proposed estimator is studied and the used algorithm for computation is discussed. Simulation studied, and real data show that the proposed robust circular estimator effectively fits JS circular models in the presence of vertical outliers and leverage points.

Microdisplacement Measurement Based on F-P Etalon: Processing Method and Experiments

Herein, a processing method is proposed for accurate microdisplacement measurements from a 2D Fabry–Perot (F-P) fringe pattern. The core of the processing algorithm uses the F-P interference imaging concentric ring pattern to accurately calculate the centre coordinates of the concentric ring. The influencing factors of measurement were analysed, and the basic idea of data processing was provided. In particular, the coordinate rotation by the 45-degree method (CR) was improved; consequently, the virtual pixel interval was reduced by half, and the calculation accuracy of the circle centre coordinate was improved. Experiments were conducted to analyse the influence of the subdivision and circle fitting methods. The results show that the proposed secondary coordinate rotation (SCR) by 45 degrees method can obtain higher accuracy of the centre coordinate than the CR method, and that the multichord averaging method (MCAM) is more suitable for calculation of the centre coordinate than the circular regression method (CRM). Displacement measurement experiments were performed. The results show that the standard experimental deviation of the centre of the circle is approximately 0.009 µm, and the extended uncertainty of the displacement measurement in the range of 5 mm is approximately 0.03 μm. The data processing method studied in this study can be widely used in the field of F-P interferometry.