Inference of microbial interactions from time series data using vector autoregression model

2013 ◽  
Author(s):  
Xingpeng Jiang ◽  
Xiaohua Hu ◽  
Weiwei Xu ◽  
Guangrong Li ◽  
Yongli Wang
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Vector Autoregression ◽  
Microbial Interactions ◽  
Series Data ◽  
Vector Autoregression Model ◽  
Autoregression Model

scholarly journals ANALISIS KAUSALITAS KEBIJAKAN FISKAL EKSPANSIF, KEBIJAKAN MONETER EKSPANSIF DAN PERTUMBUHAN EKONOMI DI INDONESIA

2020 ◽  
Vol 2 (1) ◽  
pp. 55
Author(s):  
Fadhliah Yuniwinsah ◽  
Ali Anis
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Monetary Policy ◽  
Fiscal Policy ◽  
Time Series Data ◽  
Vector Autoregression ◽  
Series Data ◽  
Vector Autoregression Model ◽  
Autoregression Model

This study examined the causality between expansionary fiscal policy, expansionary monetary policy and economic growth in Indonesia’s using a time series data with vector autoregression model (VAR) in the period of 1969-2018. The results of this study showed that are there is no causality between expansionary fiscal policy and expansionary monetary policy but there one-way relationship between them, it is the expansionary monetary policy gives influence to expansionary fiscal policy. There is no causality between expansionary fiscal policy and economic growth but there one-way relationship between them, It is economic growth gives influence to expansionary fiscal policy. And there is no causality between expansionary monetary policy and economic growth but there one-way relationship between them, it is economic growth gives influence to expansionary monetary policy.

scholarly journals INTEGRASI PASAR AYAM BROILER DI SENTRA PRODUKSI DAN PASAR INDONESIA

JURNAL PANGAN ◽  
2021 ◽  
Vol 30 (1) ◽  
pp. 31-44
Author(s):  
Jojo Jojo ◽  
Harianto Harianto ◽  
Rita Nurmalina ◽  
Dedi Budiman Hakim
Keyword(s):  
Time Series ◽  
Broiler Chickens ◽  
Broiler Chicken ◽  
Time Series Data ◽  
Vector Autoregression ◽  
Market Competition ◽  
Series Data ◽  
The West ◽  
West Java ◽  
Vector Autoregression Model

Ayam broiler  merupakan salah satu komoditas strategis yang tumbuh pesat, dihasilkan subsektor peternakan. Permasalahan umum pemasaran ayam broiler antara lain fluktuasi harga dan kompetisi pasar terhadap harga ayam antar pedagang besar antar kota menyebabkan terjadinya keterkaitan harga ayam satu kota dengan kota lainnya, antar peternak dan pedagang eceran. Tujuan penelitian ini  untuk mengkaji integrasi pasar  ayam broiler Jawa Barat dan pasar Indonesia.  Data yang digunakan merupakan data sekunder  time series bulanan, yaitu 72 bulan, periode  Januari 2014 – Desember 2019. Data dianalisis menggunakan pendekatan model VAR (Vector Autoregression). Hasil analisis menunjukkan bahwa  pasar  ayam broiler Jawa Barat tidak memiliki integrasi dengan pasar Indonesia baik dalam jangka panjang ataupun jangka pendek. Broiler chickens are a strategic commodity that is growing rapidly, produced by the livestock sub-sector. General problems of broiler chicken marketing include price fluctuations and market competition on chicken prices among wholesalers between cities, causing a linkage between the price of chickens from one city to another, between breeders and retail traders. The purpose of this study was to examine the integration of the West Java broiler market and the Indonesian market. The data used are secondary monthly time series data, namely 72 months, for the period January 2014 - December 2019. The data were analyzed using the VAR (Vector Autoregression) model approach. The results of the analysis show that the West Java broiler chicken market does not have integration with the Indonesian market either in the long or short term.  

Predicting microbial interactions from time series data with network information

2017 ◽  
Vol 17 (2) ◽  
pp. 97
Author(s):  
Yan Wang ◽  
Mingzhi Mao ◽  
Fang Li ◽  
Wenping Deng ◽  
Shaowu Shen ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Microbial Interactions ◽  
Series Data ◽  
Network Information

scholarly journals Using causality and correlation analysis to decipher microbial interactions in activated sludge

2021 ◽  
Author(s):  
Weiwei Cai ◽  
Xiangyu Han ◽  
Hong Yao
Keyword(s):  
Time Series ◽  
Activated Sludge ◽  
Network Theory ◽  
Time Series Data ◽  
Microbial Interactions ◽  
Series Data ◽  
Natural Environments ◽  
Cell Aggregate ◽  
Causality Analysis ◽  
Mutualistic Relationship

Network theory is widely used to understand microbial interactions in activated sludge and numerous other artificial and natural environments. However, when using correlation-based methods, it is not possible to identify the directionality of interactions within microbiota. Based on the classic Granger test of sequencing-based time-series data, a new Microbial Causal Correlation Network (MCCN) was constructed with distributed ecological interaction on the directed, associated links. As a result of applying MCCN to a time series of activated sludge data, we found that the hub species OTU56, classified as belonging the genus Nitrospira, was responsible for completing nitrification in activated sludge, and mainly interacted with Proteobacteria and Bacteroidetes in the form of amensal and commensal relationships, respectively. Phylogenetic tree suggested a mutualistic relationship between Nitrospira and denitrifiers. Zoogloea displayed the highest ncf value within the classified OTUs of the MCCN, indicating that it could be a foundation for activated sludge through forming the characteristic cell aggregate matrices into which other organisms embed during floc formation. Overall, the introduction of causality analysis greatly expands the ability of a network to shed a light on understanding the interactions between members of a microbial community.

scholarly journals Nonparametric Time-Series Estimation of Joint DGP, Conditional DGP, and Vector Autoregression

1985 ◽  
Vol 1 (1) ◽  
pp. 27-52 ◽  
Author(s):  
Radhey S. Singh ◽  
Aman Ullah
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Vector Autoregression ◽  
Series Data ◽  
Mixing Conditions ◽  
Conditional Mean ◽  
Nonparametric Estimators ◽  
Time Series Estimation ◽  
Series Estimation ◽  
Data Generating Process

In this paper we develop nonparametric estimators of the joint time series data generating process (DGP) of (xt,yt) at differentt-values, of conditional DGP, of the conditional mean ofxtgiven the past values ofxandy, and, more generally, the conditional mean of (xt,yt) given their past values (vector autoregression). We establish, among other results, the central limit theorems for these estimators under far weaker mixing conditions than those used in Robinson [23], where only thextseries is considered. Uniform consistency and rate results for the consistencies of various estimators are also obtained. The results of the paper are useful in light of the fact that often the functional form of the dynamic regression is not known and also the assumption of the Gaussian process is not true.

scholarly journals A Bayesian Poisson Vector Autoregression Model

2012 ◽  
Vol 20 (3) ◽  
pp. 292-315 ◽  
Author(s):  
Patrick T. Brandt ◽  
Todd Sandler
Keyword(s):  
Time Series ◽  
Dynamic Model ◽  
Vector Autoregression ◽  
Forecast Errors ◽  
Impulse Responses ◽  
Multiplier Methods ◽  
Count Time Series ◽  
Vector Autoregression Model ◽  
Count Models ◽  
Autoregression Model

Multivariate count models are rare in political science despite the presence of many count time series. This article develops a new Bayesian Poisson vector autoregression model that can characterize endogenous dynamic counts with no restrictions on the contemporaneous correlations. Impulse responses, decomposition of the forecast errors, and dynamic multiplier methods for the effects of exogenous covariate shocks are illustrated for the model. Two full illustrations of the model, its interpretations, and results are presented. The first example is a dynamic model that reanalyzes the patterns and predictors of superpower rivalry events. The second example applies the model to analyze the dynamics of transnational terrorist targeting decisions between 1968 and 2008. The latter example's results have direct implications for contemporary policy about terrorists' targeting that are both novel and innovative in the study of terrorism.

scholarly journals PENGARUH JUMLAH UANG BEREDAR (JUB) DAN EKSPOR TEMBAKAU TERHADAP KURS DI INDONESIA

2019 ◽  
Vol 2 (1) ◽  
pp. 15
Author(s):  
Siti Aryani ◽  
Murtala Murtala
Keyword(s):  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
Series Data ◽  
Analysis Model ◽  
Vector Autoregression Model ◽  
Var Analysis ◽  
Autoregression Model ◽  
The Exchange Rate ◽  
Analyze Data

This study aims to determine the effect of the money supply and export of tobacco on the exchange rate in Indonesia. This study uses time series data from 1986 to 2016. To analyze data, this uses Multiple linear regression and Vector Autoregression Model (VAR). Based on the results of the study obtained, it can be seen that partially the money supply had a positive and significant effect on the exchange rate and the export of tobacco had a negative and significant effect on the exchange rate. While simultaneously, the money supply and exports of tobacco had a positive and significant effect on the exchange rate in Indonesia. Furthermore, the results of the VAR analysis model showed that the exchange rate why influenced significantly and positively by the movement itself. The money supply had a positive and insignificant effect on the exchange rate while tobacco exports had a positive and significant effect on the exchange rate.

scholarly journals PENGARUH JUMLAH UANG BEREDAR, INFLASI DAN NILAI TUKAR RUPIAH TERHADAP PENDAPATAN NASIONAL DI INDONESIA MENGGUNAKAN MODEL DINAMIS

2019 ◽  
Vol 2 (2) ◽  
pp. 98
Author(s):  
Zakiah Zakiah ◽  
Umaruddin Usman
Keyword(s):  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
National Income ◽  
Series Data ◽  
Analysis Model ◽  
Vector Autoregression Model ◽  
Autoregression Model ◽  
One Year ◽  
Analyze Data

This study aims to determine the effect of the money supply, inflation and the rupiah exchange rate on national income in Indonesia. This study uses time series data from 1996-2017 obtained from www.bi.go.id, and www.bps.go.id. The tool used to analyze data is the Vector Autoregression Model (VAR) with the Impulse Respo Function (IRF). Based on research that uses the results of the VAR analysis model which shows that there is a unidirectional relationship between the variable money supply to national income and the unidirectional relationship between national income and the rupiah exchange rate. The results of the study with the analysis of the response response of the money supply took one year, the inflation variable took four years, and the exchange rate variable took three years to be stable after the shock caused by other variables in the study.

scholarly journals Budget deficit-macroeconomic variables nexus in Kenya

2021 ◽  
Vol 43 ◽  
pp. 270-292
Author(s):  
Doris Syombua Philip ◽  
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Budget Deficit ◽  
Vector Autoregression ◽  
Negative Impact ◽  
External Debt ◽  
Series Data ◽  
Macroeconomic Variables ◽  
Vector Autoregression Model ◽  
Autoregression Model

Aim/purpose – The aim of this paper was to establish the nexus between a budget defi- cit and selected macroeconomic variables in Kenya. This adds to the existing literature while the methodology and choice of the econometric tools used improve the predictabil- ity of the link between a budget deficit and macroeconomic variables. The results are relevant to policy makers as they may help improve understanding of budget deficit management. Design/methodology/approach – The study used time series data for the period from 1976 to 2018 and employed the Vector Autoregression model reinforced by the Keynesian Mundell–Fleming framework. Findings – The impulse response function derived from the vector autoregression model revealed that shocks from both interest rate and exchange rate had a positive impact on budget deficit. External debt servicing and current account deficit shocks had a negative impact on the budget deficit. Research implications/limitations – Interest rate and exchange rate policies remain key in reducing the growth of the budget deficit. Policies on external debt servicing, such as timely payment of debts and prudent investment of borrowed funds, will also reduce the budget deficit. Originality/value/contribution – The study employed transmission mechanism which involves multiple equations to establish the nexus between a budget deficit and macroe- conomic variables in Kenya. Keywords: budget deficit; selected macroeconomic variables, Kenya. JEL Classification: H60, H62, H68.

scholarly journals PENGARUH INFLASI, PENGELUARAN PEMERINTAH DAN EKSPOR TERHADAP PERTUMBUHAN EKONOMI DI INDONESIA

2019 ◽  
Vol 2 (1) ◽  
pp. 37
Author(s):  
Yusra Mahzalena ◽  
Hijri Juliansyah
Keyword(s):  
Economic Growth ◽  
Government Spending ◽  
Time Series Data ◽  
Series Data ◽  
Analysis Tool ◽  
Analysis Model ◽  
Vector Autoregression Model ◽  
Var Analysis ◽  
Insignificant Effect ◽  
Autoregression Model

The purpose of this study was to determine the effect of inflation, Government spending, and exports on economic growth in Indonesia during 1990-2016. This study used time series data obtained from the Central Bureau of Statistics. The number of samples in this study was 27 years as the object of this research. This study used a Vector Autoregression Model (VAR) analysis tool with the help of Eviews 9 software. The results of the VAR analysis model showed that economic growth was insignificantly and positively influenced by its movements, inflation had a positive and insignificant effect on economic growth, and Government spending had a positive and insignificant effect on economic growth, while exports had a negative and insignificant effect on economic growth.

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