Estimation of the transfer function by autoregressive deconvolution techniques?An application to time series analysis

1992 ◽  
Vol 24 (5) ◽  
pp. 479-498 ◽  
Author(s):  
Y. S. Kang ◽  
J. J. Royer ◽  
Cl. Chambon ◽  
L. Demassieux
Keyword(s):  
Time Series ◽  
Transfer Function ◽  
Time Series Analysis ◽  
Series Analysis ◽  
Deconvolution Techniques

scholarly journals PERAMALAN JUMLAH PENDERITA DEMAMBER DARAH DENGUE DI KABUPATEN JOMBANG JAWA TIMUR DENGAN PENDEKATAN FUNGSI TRANSFER SINGLE INPUT

2018 ◽  
Vol 15 (2) ◽  
pp. 10
Author(s):  
Sediono Sediono
Keyword(s):  
Time Series ◽  
Transfer Function ◽  
Time Series Analysis ◽  
Dengue Fever ◽  
Stationary Time Series ◽  
Transfer Function Model ◽  
Function Model ◽  
Series Analysis ◽  
Future Data ◽  
Single Input

AbstractForecasting  is an important things in time series analysis, because by obtaining a convenient model that is statictically appropriate. Clearly, that can be used to predict the structure of future data form. Transfer function is one of mathematical model  in time series analysis, that can be used to forecasting time index data both univariate and multivariate. Transfer function describes the predictive value  of the output series (Yt) based on the value of one or more input series(Xt). The single input transfer function model is a transfer function model that uses one variable as input series (Xt), where each series of both input series and output series must be a stationary time series model, both stationary in the mean and stationary in variant. One of the used transfer function is to govern a model and forecasting of the number of cases dengue fever (Yt) in Kabupaten Jombang, East Java, where the input variable based on data of rainfall (Xt). From the result of this study was obtained that model of transfer function has a equation Y𝑡 = 0,0542X𝑡+  (1 − 0,7309𝐵)(1 + 0,6568𝐵12) with parameter ωo = 0.0542, ∅1 = 0.7309 and  Φ12 = -0.6568. From the model, it can be interpreted that the number of dengue sufferers for a particular month was influenced by the rainfall on those month and the months before. According to the model of the transfer function, it can be used to forecast the number of sufferers of dengue fever in Kabupaten Jombang  for period next 20 months. After compared between data of forecasting and actual data, there exists equally  trend, namely 15 months of 20 month that are forecasted, such that  it can be explain that majority 75% of the results of forecasting in this study are valid. Keywords: forecasting , single input transfer function, stationer point, Dengue fever  Abstrak Peramalan adalah sesuatu hal yang penting dalam analisis runtun waktu, karena dengan diperolehnya sebuah model yang tepat secara statistik, jelas hal tersebut dapat digunakan untuk memprediksi struktur pola data yang akan datang. Fungsi transfer merupakan salah satu model matematis dalam analisis runtun waktu  yang dapat digunakan untuk  peramalan data indekswaktu baik univariat maupun multivariat. Fungsi transfer menggambarkan nilai prediksi  dari  output series (Yt) berdasarkan nilai satu atau lebih input series (Xt). Model fungsi transfer  single input  adalah model fungsi transfer yang menggunakan satu variabel sebagai input series (Xt), dimana masing-masing series baik input series maupun output series keduanya harus sama-sama merupakan model runtun waktu yang stasioner, baik stasioner dalam mean maupun stasioner dalam varian. Salah satu penggunaan  model fungsi transfer ini adalah untuk pembuatan model dan peramalan jumlah kasus demam berdarah dengue (Yt)  di Kabupaten Jombang Jawa Timur, dengan variabel inputnya berdasarkan data curah hujan (Xt). Dari hasil penelitian diperoleh  model fungsi transfer yang memiliki persamaan  Y𝑡 = 0,0542X𝑡 +  (1 − 0,7309𝐵)(1 + 0,6568𝐵12) 𝑎𝑡 , dengan parameter ωo = 0,0542, ∅1 = 0,7309, dan Φ12 = -0,6568. Dari model tersebut dapat diinterpretasikan bahwa jumlah penderita demam berdarah dengue pada suatu bulan dipengaruhi curah hujan pada bulan itu, dan dipengaruhi oleh beberapa gangguan pada bulan-bulan sebelumnya. Selanjutnya berdasarkan model fungsi transfer tersebut dapat digunakan untuk peramalan jumlah penderita demam berdarah dengue di Kabupaten Jombang untuk periode 20 bulan kedepan. Setelah dilakukan perbandingan antara data hasil peramalan dengan data aktual, terdapat kesamaan trend yaitu sejumlah 15 bulan dari 20 bulan yang diramalkan, sehingga dapat dijelaskan bahwa sebagian besar yaitu 75% dari hasil peramalan  dalam penelitian ini adalah valid. Kata Kunci : Peramalan, Fungsi transfer single input, stasioner, Demam Berdarah Dengue. 

Dynamical Peculiarities of Concatenational Changes in Functional Cardiovascular Parameters

2018 ◽  
Vol 3 (82) ◽  
Author(s):  
Eurelija Venskaitytė ◽  
Jonas Poderys ◽  
Tadas Česnaitis
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Functional State ◽  
The Body ◽  
Functional Changes ◽  
High Intensity Training ◽  
Series Analysis ◽  
Greco Roman ◽  
St Segment ◽  
Standard Lead

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.

The Contribution of Foreign Direct Investment for Economic Growth of Ethiopia: Time Series Analysis

2018 ◽  
Vol 9 (02) ◽  
Author(s):  
Addissie Melak
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Foreign Direct Investment ◽  
Time Series Analysis ◽  
Direct Investment ◽  
Policy Framework ◽  
Annual Growth Rate ◽  
African Countries ◽  
Series Analysis ◽  
Integration Test

Economic growth of countries is one of the fundamental questions in economics. Most African countries are opening their economies for welcoming of foreign investors. As such Ethiopia, like many African countries took measures to attract and improve foreign direct investment. The purpose of this study is to examine the contribution of foreign direct investment (FDI) for economic growth of Ethiopia over the period of 1981-2013. The study shows an overview of Ethiopian economy and investment environment by the help of descriptive and econometric methods of analysis to establish empirical investigation for the contribution of FDI on Ethiopian economy. OLS method of time series analysis is employed to analyse the data. The stationary of the variables have been checked by using Augmented Dickey Fuller (ADF) Unit Root test and hence they are stationery at first difference. The co- integration test also shows that there is a long run relationship between the dependent and independent variables. Accordingly, the finding of the study shows that FDI, GDP per capita, exchange rate, total investment as percentage of GDP, inflow of FDI stock, trade as percentage of GDP, annual growth rate of GDP and liberalization of the economy have positive impact on Ethiopian GDP. Whereas Gross fixed domestic investment, inflows of FDI and Gross capital formation influence economic growth of Ethiopia negatively. This finding suggests that there should be better policy framework to attract and improve the volume of FDI through creating conducive environment for investment.

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