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1. Inflation and Bitcoin: A descriptive time-series analysis

Author:
Blau, Benjamin M.; Griffith, Todd G.; Whitby, Ryan J.
Source:
Economics letters 2021 v.203 pp. 109848
ISSN:
0165-1765
Subject:
time series analysis,   etc   ; blockchain; inflation; prices;     Show all 4 Subjects
Abstract:
... This study examines the time-series relation between Bitcoin and forward inflation expectation rates. Using a vector autoregressive process, we find that changes in Bitcoin Granger cause changes in the forward inflation rate. Furthermore, imposing an exogenous shock to Bitcoin’s price results in a persistent increase in the forward inflation rate. Our findings provide support for the notion that B ...
DOI:
10.1016/j.econlet.2021.109848

2. Application of multiple approaches to investigate hydraulic connection in multiple aquifers system in coalfield

Author:
Qu, Shen; Shi, Zheming; Wang, Guangcai; Han, Jiaqian
Source:
Journal of hydrology 2021 v.595 pp. 125673
ISSN:
0022-1694
Subject:
time series analysis,   etc   ; aquifers; coal; geophysics; hydrochemistry;     Show all 5 Subjects
Abstract:
... Understanding the hydraulic connections between overburden aquifers is key to safe coal mining. However, accurately identifying such connections remains challenging. Conventional investigation methods include geophysical investigation, pumping test, and hydrochemical analysis, which are time-consuming, expensive, and cannot determine continuous variations in hydraulic connection. In this paper, we ...
DOI:
10.1016/j.jhydrol.2020.125673

3. An Enhanced Innovative Triangular Trend Analysis of Rainfall Based on a Spectral Approach

Author:
Zerouali, Bilel; Al-Ansari, Nadhir; Chettih, Mohamed; Mohamed, Mesbah; Abda, Zaki; Santos, Celso Augusto Guimarães; Zerouali, Bilal; Elbeltagi, Ahmed
Source:
Water 2021 v.13 no.5
ISSN:
2073-4441
Subject:
time series analysis,   etc   ; rain; water; wavelet; Algeria;     Show all 5 Subjects
Abstract:
... The world is currently witnessing high rainfall variability at the spatiotemporal level. In this paper, data from three representative rain gauges in northern Algeria, from 1920 to 2011, at an annual scale, were used to assess a relatively new hybrid method, which combines the innovative triangular trend analysis (ITTA) with the orthogonal discrete wavelet transform (DWT) for partial trend identif ...
DOI:
10.3390/w13050727

4. Inferring species interactions using Granger causality and convergent cross mapping

Author:
Barraquand, Frédéric; Picoche, Coralie; Detto, Matteo; Hartig, Florian
Source:
Theoretical ecology 2021 v.14 no.1 pp. 87-105
ISSN:
1874-1738
Subject:
time series analysis,   etc   ; dynamic models; prediction;     Show all 3 Subjects
Abstract:
... Identifying directed interactions between species from time series of their population densities has many uses in ecology. This key statistical task is equivalent to causal time series inference, which connects to the Granger causality (GC) concept: x causes y if x improves the prediction of y in a dynamic model. However, the entangled nature of nonlinear ecological systems has led to question the ...
DOI:
10.1007/s12080-020-00482-7

5. Unifying ecosystem responses to disturbance into a single statistical framework

Author:
Lemoine, Nathan P.
Source:
Oikos 2021 v.130 no.3 pp. 408-421
ISSN:
0030-1299
Subject:
time series analysis,   etc   ; anthropogenic activities; ecosystems;     Show all 3 Subjects
Abstract:
... Natural ecosystems are currently experiencing unprecedented rates of anthropogenic disturbance. Given the potential ramifications of more frequent disturbances, it is imperative that we accurately quantify ecosystem responses to severe disturbance. Specifically, ecologists and managers need estimates of resistance and recovery from disturbance that are free of observation error, not biased by temp ...
DOI:
10.1111/oik.07752

6. Not All Thin Markets Are Alike: The Case of Organic and Non‐genetically Engineered Corn and Soybeans

Author:
Raszap Skorbiansky, Sharon; Adjemian, Michael K
Source:
Journal of agricultural economics 2021 v.72 no.1 pp. 117-133
ISSN:
0021-857X
Subject:
time series analysis,   etc   ; agricultural economics; corn;     Show all 3 Subjects
Abstract:
... We use time series methods to explore the relationship between prices for two different niche versions of feed corn and soybeans, and their conventional counterparts. Whereas organic versions are linearly cointegrated, and their premia are high and stable, non‐GE products – which are nonlinearly cointegrated – exhibit narrower premia that are subject to collapse. Because organics are also non‐GE, ...
DOI:
10.1111/1477-9552.12393

7. Bootstrapping non-stationary stochastic volatility

Author:
Boswijk, H. Peter; Cavaliere, Giuseppe; Georgiev, Iliyan; Rahbek, Anders
Source:
Journal of econometrics 2021
ISSN:
0304-4076
Subject:
time series analysis,   etc   ; probability; stochastic processes; variance;     Show all 4 Subjects
Abstract:
... In this paper we investigate to what extent the bootstrap can be applied to conditional mean models, such as regression or time series models, when the volatility of the innovations is random and possibly non-stationary. In fact, the volatility of many economic and financial time series displays persistent changes and possible non-stationarity. However, the theory of the bootstrap for such models ...
DOI:
10.1016/j.jeconom.2021.01.005

8. Hidden Markov models identify major movement modes in accelerometer and magnetometer data from four albatross species

Author:
Conners, Melinda G.; Michelot, Théo; Heywood, Eleanor I.; Orben, Rachael A.; Phillips, Richard A.; Vyssotski, Alexei L.; Shaffer, Scott A.; Thorne, Lesley H.
Source:
Movement ecology 2021 v.9 no.1 pp. 7
ISSN:
2051-3933
Subject:
time series analysis,   etc   ; accelerometers; data collection; life history;     Show all 4 Subjects
Abstract:
... BACKGROUND: Inertial measurement units (IMUs) with high-resolution sensors such as accelerometers are now used extensively to study fine-scale behavior in a wide range of marine and terrestrial animals. Robust and practical methods are required for the computationally-demanding analysis of the resulting large datasets, particularly for automating classification routines that construct behavioral t ...
DOI:
10.1186/s40462-021-00243-z

9. Identifying resting locations of a small elusive forest carnivore using a two-stage model accounting for GPS measurement error and hidden behavioral states

Author:
Hance, Dalton J.; Moriarty, Katie M.; Hollen, Bruce A.; Perry, Russell W.
Source:
Movement ecology 2021 v.9 no.1 pp. 17
ISSN:
2051-3933
Subject:
time series analysis,   etc   ; Oregon; accelerometers; animals; carnivores; forests; statistical models;     Show all 7 Subjects
Abstract:
... BACKGROUND: Studies of animal movement using location data are often faced with two challenges. First, time series of animal locations are likely to arise from multiple behavioral states (e.g., directed movement, resting) that cannot be observed directly. Second, location data can be affected by measurement error, including failed location fixes. Simultaneously addressing both problems in a single ...
DOI:
10.1186/s40462-021-00256-8

10. Networks of stress, affect and eating behaviour: anticipated stress coping predicts goal-congruent eating in young adults

Author:
Pannicke, Björn; Kaiser, Tim; Reichenberger, Julia; Blechert, Jens
Source:
Theinternational journal of behavioral nutrition and physical activity 2021 v.18 no.1 pp. 9
ISSN:
1479-5868
Subject:
time series analysis,   etc   ; energy; females; healthy diet; hunger; physical activity;     Show all 6 Subjects
Abstract:
... BACKGROUND: Many people aim to eat healthily. Yet, affluent food environments encourage consumption of energy dense and nutrient-poor foods, making it difficult to accomplish individual goals such as maintaining a healthy diet and weight. Moreover, goal-congruent eating might be influenced by affects, stress and intense food cravings and might also impinge on these in turn. Directionality and inte ...
DOI:
10.1186/s12966-020-01066-8

11. Uncovering the evolution of tin use in the United States and its implications

Author:
Yang, Congren; Zeng, Xianlai; Li, Haodong; Tian, Zuyuan; Liu, Wei; Qin, Wenqing; Li, Jinhui
Source:
Frontiers of environmental science & engineering 2021 v.15 no.6 pp. 118
ISSN:
2095-2201
Subject:
time series analysis,   etc   ; environmental science; humans; tin; China;     Show all 5 Subjects
Abstract:
... Tin is of key importance to daily life and national security; it is considered an essential industrial metal. The United States (US) is the world’s largest economy and consumer of natural resources. Therefore, the analysis of historical tin use in the US is helpful for understanding future tin use trends in the world as a whole and in developing countries. Time series analysis, regression analysis ...
DOI:
10.1007/s11783-021-1406-6

12. Robust tests for time series comparison based on Laplace periodograms

Author:
Jin, Lei
Source:
Computational statistics & data analysis 2021 v.160 pp. 107223
ISSN:
0167-9473
Subject:
time series analysis,   etc   ; Monte Carlo method; mechanical damage; vibration;     Show all 4 Subjects
Abstract:
... Statistical comparison of time series is useful for the detection of mechanical damage and many other real-world applications. New methods have been proposed to check whether two semi-stationary time series have the same normalized dynamics. The proposed methods differ from traditional methods in that they are based on the Laplace periodogram, which is a robust tool to analyze the serial dependenc ...
DOI:
10.1016/j.csda.2021.107223

13. High dimensional regression for regenerative time-series: An application to road traffic modeling

Author:
Bouchouia, Mohammed; Portier, François
Source:
Computational statistics & data analysis 2021 v.158 pp. 107191
ISSN:
0167-9473
Subject:
time series analysis,   etc   ; algorithms; prediction; risk; roads; traffic; urban areas;     Show all 7 Subjects
Abstract:
... A statistical predictive model in which a high-dimensional time-series regenerates at the end of each day is used to model road traffic. Due to the regeneration, prediction is based on a daily modeling using a vector autoregressive model that combines linearly the past observations of the day. Due to the high-dimension, the learning algorithm follows from an ℓ1-penalization of the regression coeff ...
DOI:
10.1016/j.csda.2021.107191

14. Statistical and temporal analysis of a novel multivariate time series data for food engineering

Author:
Abdella, Alla; Brecht, Jeffrey K.; Uysal, Ismail
Source:
Journal of food engineering 2021 v.298 pp. 110477
ISSN:
0260-8774
Subject:
time series analysis,   etc   ; data collection; descriptive statistics; temperature;     Show all 4 Subjects
Abstract:
... In this paper, we conduct a statistical and temporal analysis to analyze dynamic factors for the temporal heterogeneity, complexity, similarity, and discrepancy on a novel location aware multivariate time series dataset. The dataset represents the temperature variations across 6 different shipments with 9 sensors in each shipment monitoring and recording sensory data at 15− min intervals across mu ...
DOI:
10.1016/j.jfoodeng.2021.110477

15. Detection of rainstorm pattern in arid regions using MODIS NDVI time series analysis

Author:
Hereher, Mohamed E.
Source:
Geocarto international 2021 v.36 no.8 pp. 861-873
ISSN:
1752-0762
Subject:
time series analysis,   etc   ; freshwater; normalized difference vegetation index; West Asia;     Show all 4 Subjects
Abstract:
... The normalized difference vegetation index (NDVI) was used to delineate potential water suppliers west of the Arabian Peninsula. Time series NDVI data extracted from the moderate resolution imaging spectroradiometer NDVI product were used to develop a robust estimate of rainstorm frequency and intensity. A total of 216 NDVI images were acquired between February 2000 and January 2018 to carry out t ...
DOI:
10.1080/10106049.2019.1629643

16. Autoregressive models for matrix-valued time series

Author:
Chen, Rong; Xiao, Han; Yang, Dan
Source:
Journal of econometrics 2021 v.222 no.1 pp. 539-560
ISSN:
0304-4076
Subject:
time series analysis,   etc   ; econometric models; economic indicators; economic theory; finance;     Show all 5 Subjects
Abstract:
... In finance, economics and many other fields, observations in a matrix form are often generated over time. For example, a set of key economic indicators are regularly reported in different countries every quarter. The observations at each quarter neatly form a matrix and are observed over consecutive quarters. Dynamic transport networks with observations generated on the edges can be formed as a ma ...
DOI:
10.1016/j.jeconom.2020.07.015

17. Decomposing anomalies

Author:
Boubaker, Sabri; Li, Bo; Liu, Zhenya; Zhang, Yifan
Source:
Economics letters 2021 v.202 pp. 109835
ISSN:
0165-1765
Subject:
time series analysis,   etc   ; prices; principal component analysis; profitability; stock exchange;     Show all 5 Subjects
Abstract:
... This paper introduces the functional principal component analysis approach for decomposing the panel returns of the anomaly-sorted portfolios. Using the US stock market data covering July 1963–July 2020, our findings indicate that the Fama–French (F–F) market factor can be captured by the first empirical functional principal component in the time-series. For the other F–F anomalies, market capital ...
DOI:
10.1016/j.econlet.2021.109835

18. Predicting use of resources by dairy cows using time series

Author:
Salau, J.; Krieter, J.
Source:
Biosystems engineering 2021 v.205 pp. 146-151
ISSN:
1537-5110
Subject:
time series analysis,   etc   ; Holstein; barns; herds; loose housing; Germany;     Show all 6 Subjects
Abstract:
... A loose-housing barn in Northern Germany with thirty-six Holstein Friesian dairy cows was fully monitored by video cameras. The barn was partitioned into the areas for lying cubicles, moving area, licking stone, cow brush, feeding and water troughs. From automatically detected cow activity, the cows’ proportional usage of the resources associated with these areas was determined. The resulting time ...
DOI:
10.1016/j.biosystemseng.2021.03.005

19. Principal component analysis using frequency components of multivariate time series

Author:
Sundararajan, Raanju R.
Source:
Computational statistics & data analysis 2021 v.157 pp. 107164
ISSN:
0167-9473
Subject:
time series analysis,   etc   ; frequency; models; principal component analysis; variance; wind;     Show all 6 Subjects
Abstract:
... Dimension reduction techniques for multivariate time series decompose the observed series into a few useful independent/orthogonal univariate components. A spectral domain method is developed for multivariate second-order stationary time series that linearly transforms the observed series into several groups of lower-dimensional multivariate subseries. These multivariate subseries have non-zero sp ...
DOI:
10.1016/j.csda.2020.107164

20. The performance of classification and forecasting Dong Nai River water quality for sustainable water resources management using neural network techniques

Author:
Hien Than, Nguyen; Dinh Ly, Che; Van Tat, Pham
Source:
Journal of hydrology 2021 v.596 pp. 126099
ISSN:
0022-1694
Subject:
time series analysis,   etc   ; neural networks; river water; rivers; water quality;     Show all 5 Subjects
Abstract:
... This study has classified and predicted the water quality for the Dong Nai river at different times. The data mining techniques were used to screen out unreliable data. The neural network model FFNN in the form of architecture I(8)-HL(9)-O(1) has been successfully developed to classify the water quality of the Dong Nai river during the period from 2012 to 2019. For this model, the RMSE values for ...
DOI:
10.1016/j.jhydrol.2021.126099