Stability and Change in European Electorates

1977 ◽  
Vol 29 (4) ◽  
pp. 523-551 ◽  
Author(s):  
Alan Zuckerman ◽  
Mark Irving Lichbach
Keyword(s):  
Voting Behavior ◽  
Time Series Data ◽  
Panel Study ◽  
Marked Change ◽  
West Germany ◽  
Series Data ◽  
Social Categories ◽  
The Social ◽  
Analyze Time Series Data ◽  
Analyze Time Series

Arguing counter to the accepted positions of political sociology, we contend that voters' decisions are best explained by the absence or presence of strong loyalties to political parties rather than by social or economic factors. Hence, in areas where most people have strong party attachments, marked change in the partisan division of the vote occurs only when an exceptionally large number of new voters enters the electoral arena; alterations in the social composition of a party's voters follow changes in the occupation or social categories of those who consistently vote for the party. In presenting this argument, we analyze time-series data for Britain, West Germany, and Sweden which negate the predicted development of “catch-all” electorates, and we test the relative power of party and class variables as predictors of voting behavior in Butler's and Stokes's panel study of British voters between 1963 and 1970.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHIKURS RUPIAH TERHADAP YEN TAHUN 1970 - 2002: ERROR CORRECTION MODEL (ECM)

2017 ◽  
Vol 6 (2) ◽  
pp. 187
Author(s):  
Nurul Yuniataqwa Karunia ◽  
Malik Cahyadin
Keyword(s):  
Exchange Rate ◽  
Time Series Data ◽  
Series Data ◽  
Short Term ◽  
Correction Model ◽  
Monetary Approach ◽  
Independent Variable ◽  
Analyze Time Series Data ◽  
Analyze Time Series ◽  
Variable Exchange

This research aims to find out factors influencing the exchange rate of rupiah toward yen. The approach used to analyze time series data in this study is monetary approach with ECM as the chosen regression model. The year of observation was begun in 1970-2002. Based on regression which done, the result showed that there is the significant correlation between independent variable (MI,Yreal, NP1) with dependent variable (exchange rate of Rupiah fYen). The correlation happens either in long or short term.

WAVELET ANALYSIS OF TIME-SERIES: COHERENT STRUCTURES, CHAOS AND NOISE

1999 ◽  
Vol 09 (03) ◽  
pp. 455-471 ◽  
Author(s):  
W. J. STASZEWSKI ◽  
K. WORDEN
Keyword(s):  
Time Series ◽  
Wavelet Analysis ◽  
Coherent Structures ◽  
Wavelet Transforms ◽  
Time Series Data ◽  
Series Data ◽  
Different Types ◽  
Analyze Time Series Data ◽  
Analyze Time Series ◽  
Analysis Of Time Series

The continuous and orthogonal wavelet transforms are used to analyze time-series data. The analysis involves signal decomposition into scale components using both Grossman–Morlet and Daubechies type wavelets. A number of simulated and experimental data vectors exhibiting different types of coherent structures, chaos and noise is analyzed. The study shows that wavelet analysis provides a unifying framework for the description of many phenomena in time-series.

scholarly journals Peramalan Banyaknya Pengunjung Pantai Glagah Menggunakan Metode Autoregressive Integrated Moving Average Exogenous (ARIMAX) dengan Efek Variasi Kalender

2019 ◽  
Vol 1 (2) ◽  
pp. 70
Author(s):  
Solikhah Novita Intan ◽  
Etik Zukhronah ◽  
Supriyadi Wibowo
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Moving Average ◽  
Series Data ◽  
Autoregressive Integrated Moving Average ◽  
Tourist Destinations ◽  
The Future ◽  
Analyze Time Series Data ◽  
Analyze Time Series

<pre>Glagah Beach is one of the tourist destinations in Kulon Progo Regency, Yogyakarta which is the most visited by tourists. Glagah Beach visitors data show  that in the month of Eid Al-Fitr there was a significant increase. This shows that there is an effect of the calendar variation of Eid al-Fitr. Therefore, it is needed a method that can be used to analyze time series data which contains effects of calendar variations, that is ARIMAX method. The aim of this study are to find the best ARIMAX model and to predict the number of visitors to Glagah Beach in the future. The result shows that the best ARIMAX model was ARIMAX([24],0,0). Forecasting from January to September 2016 are 37211, 21306, 26247, 24148, 28402, 29309, 81724, 26029, and 23688 visitors.</pre><br /> Keywords: Glagah Beach; variation of calendar; Eid al-Fitr; ARIMAX.

scholarly journals Stochastic methods for inferring states of cell migration

2018 ◽  
Author(s):  
R.J. Allen ◽  
C. Welch ◽  
N. Pankow ◽  
K. Hahn ◽  
Timothy C. Elston
Keyword(s):  
Time Series ◽  
Cell Migration ◽  
Time Series Data ◽  
Cell Movement ◽  
Series Data ◽  
Stochastic Methods ◽  
Spatiotemporal Regulation ◽  
Rho Family ◽  
Analyze Time Series Data ◽  
Analyze Time Series

AbstractCell migration refers to the ability of cells to translocate across a substrate or through a matrix. To achieve net movement requires spatiotemporal regulation of the actin cytoskeleton. Computational approaches are neceary to identify and quantify the regulatory mechanisms that generate directed cell movement. To address this need, we developed computational tools, based on stochastic modeling, to analyze time series data for the position of randomly migrating cells. Our approach allows parameters that characterize cell movement to be efficiently estimated from time series data. We applied our methods to analyze the random migration of Mouse Embryonic Fibroblasts (MEFS). Our analysis revealed that these cells exist in two distinct states of migration characterized by differences in cell speed and persistence. Further analysis revealed that the Rho-family GTPase RhoG plays a role in establishing these two states. An important feature of our computational approach is that it provides a method for predicting the current migration state of an individual cell from time series data. Using this feature, we demonstrate that HeLa cells also exhibit two states of migration, and that these states correlate with differences in the spatial distribution of active Rac1.

A Mathematical Database to Process Time Series

2018 ◽  
Vol 14 (3) ◽  
pp. 1-21
Author(s):  
Cyrille Ponchateau ◽  
Ladjel Bellatreche ◽  
Carlos Ordonez ◽  
Mickael Baron
Keyword(s):  
Time Series ◽  
Mathematical Models ◽  
Time Series Data ◽  
Series Data ◽  
Process Time ◽  
Data Store ◽  
Database Structure ◽  
Analyze Time Series Data ◽  
Analyze Time Series ◽  
Over Time

In scientific research, the results of an experiment commonly take the form of a time series, in which such time series consists of measurements collected from a sensor over time. After time series are stored, mathematical models are derived using numerical methods. Even though there exist plenty of tools to store and analyze time series data, there is scarce research aimed at storing and querying derived models, which are the most important mechanism for a scientist to understand data. In this article, the authors propose to help scientists with a flexible database structure to persist and manage mathematical models with a mathematical models store, with extended features, to handle time series. In this article, the authors introduce the concept of a mathematical models store enriched with numerical processing methods to allow queries based on raw time series data. Then they introduce a prototype, that is an implementation of such a data store with PostgreSQL.

scholarly journals Has Social Sector Development Catalysed the Inclusiveness of India’s Economic Growth?

2020 ◽  
Vol 68 (1) ◽  
pp. 61-81
Author(s):  
Vikram Chadha ◽  
Ishu Chadda
Keyword(s):  
Time Series Data ◽  
Negative Association ◽  
Series Data ◽  
Inclusive Growth ◽  
Social Sector ◽  
Poverty And Inequality ◽  
The Social ◽  
Development Policies ◽  
The Impact ◽  
Social Sectors

The study attempts to examine the impact of social sector development on inclusive growth in India. Ever since Independence, India’s encounter with gnawing poverty and stark deprivation, particularly of the weaker and the marginalised sections of society, cajoled India’s planners to moot the development policies with the sole objective of exacerbating growth with equity. That is why since the beginning of the planning era, the stress had been laid on strengthening and expanding the social sectors with the premise that it would boost the inclusive growth agenda, manifesting in equal access to employment and economic opportunities; equal participation in decision-making and reduction in poverty and inequality. In conformity with the objective of our study, we intend to gauge the effect and contribution of different components of social sector development in India, on inclusiveness of growth using time series data for the period of 1985–1986 to 2015–2016. It was found that the expenditure related to ‘social security and welfare’ contributes significantly towards inclusive growth in India while the expenditure incurred on ‘welfare of marginalised class’ and ‘rural development’ exudes negative association with inclusiveness of growth.

Regional and Industrial Wage Dynamics in West Germany and the United States / Regionale und industrielle Lohndynamik in Westdeutschland und den USA

2002 ◽  
Vol 222 (5) ◽  
Author(s):  
Antje Mertens
Keyword(s):  
United States ◽  
Time Series Data ◽  
The United States ◽  
Labour Markets ◽  
West Germany ◽  
Series Data ◽  
Labour Demand ◽  
Wage Dynamics ◽  
Demand Shocks ◽  
Individual Level

SummaryIt is commonly known that every economy is faced with the problem of unevenly distributed labour demand changes across industries, occupations and regions. In competitive labour markets flexible wages and the mobility of labour would lead to a new equilibrium distribution of wages and employment. Regional or industrial unemployment dispersion in Germany is often blamed on a lack of wage adjustments and the lack of labour mobility when economic fortunes are not distributed evenly, but this hypothesis is hardly ever tested. This paper asks how wage reactions in Germany compare with responses in the United States using individual level data. As a first step labour demand shocks are estimated from employment time series data using deterministic detrending and the Hodrick-Prescott filter. These are then included in typical wage regressions based on micro data. The results propose that German labour markets are not as inflexible as simple evidence might suggest. Although wages are regionally only flexible in the United States, wages are found to react to industrial labour demand shocks in both countries. Especially for more experienced and therefore less mobile groups in the German labour market wages react to industrial labour demand shocks.

scholarly journals Multiple Linear Regression to Forecast Balance of Trade

2014 ◽  
Vol 7 (2) ◽  
Author(s):  
Sarimah Omar Gan ◽  
Sabri Ahmad
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Time Series Data ◽  
Series Data ◽  
External Trade ◽  
The Social ◽  
Balance Of Trade ◽  
Import And Export ◽  
The Relationship

The main objective of this study is to build a regression model by using multiple linear regression (MLR) analysis. MLR will be used when there are two or more controlled variables involved in the relationship. There are four general steps in building a regression model which are checking assumptions, selecting suitable methods of MLR, interpreting the output and selecting the best MLR model. The objective will be evaluated by using a time series data that have been obtained from Monthly Statistical Bulletin Sabah, Department of Statistics Malaysia, Sabah which is from year 2003 to 2009. The monthly data of external trade in Sabah in term of import and export totals for seven years will be analysed by using Statistical Package for the Social Sciences (SPSS) Statistics Version 17.0. Balance of trade for year 2011 and above can be forecasted through the regression model that has been developed by using MLR analysis.

Decision Making Strategy Based on Time Series Data of Voting Behavior

2015 ◽  
pp. 229-241
Author(s):  
Shogo Higuchi ◽  
Ryohei Orihara ◽  
Yuichi Sei ◽  
Yasuyuki Tahara ◽  
Akihiko Ohsuga
Keyword(s):  
Decision Making ◽  
Time Series ◽  
Voting Behavior ◽  
Time Series Data ◽  
Series Data
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