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Journal articles on the topic 'Stationarity'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences 18, no. 10 (2014): 4065–76. http://dx.doi.org/10.5194/hess-18-4065-2014.

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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall

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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences Discussions 11, no. 6 (2014): 6311–42. http://dx.doi.org/10.5194/hessd-11-6311-2014.

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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall

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3

Fan, Gai Ling, and Zhi Hua Huang. "Stationarity of the EEG Segment with Event-Related Potentials." Applied Mechanics and Materials 148-149 (December 2011): 30–33. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.30.

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EEG (electroencephalography), as a noninvasive and inexpensive method, is widely used to measure brain function and make inferences about regional brain activity. The stationarity of EEG has been investigated by many researchers, while the stationarity of EEG segment with ERPs (Event-related Potentials) has hardly been concerned about. It is necessary to analyze the stationarity of this kind of EEG. In this paper, we concentrate on the stationarity of the EEG with ERPs by testing the stationarity of 500ms EEG segments with ERPs recorded from six subjects in two types of experiments. The result

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4

Omotoye, Evelyn, and Bunmi Rotimi. "Stationarity in Prophet Model Forecast: Performance Evaluation Approach." American Journal of Theoretical and Applied Statistics 14, no. 3 (2025): 109–17. https://doi.org/10.11648/j.ajtas.20251403.12.

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Stationarity plays a crucial role in time series analysis, significantly influencing model performance and the reliability of forecasts. Despite its importance, many real-world datasets exhibit non-stationary behaviour, which can lead to misleading or spurious forecasting outcomes. This study explores the impact of stationarity on the performance of the Prophet Model, a scalable time series forecasting tool developed by Facebook, by comparing forecasts from both stationary and non-stationary versions of the same dataset. The monthly international airline passenger data was downloaded from the

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Shen, Yi, and Tony S. Wirjanto. "Stationarity as a path property." Probability and Mathematical Statistics 39, no. 2 (2019): 403–22. http://dx.doi.org/10.19195/0208-4147.39.2.9.

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Traditionally, stationarity refers to shift invariance of the distribution of a stochastic process. In this paper, we rediscover stationarity as a path property instead of a distributional property. More precisely, we characterize a set of paths, denoted by A, which corresponds to the notion of stationarity. On one hand, the set A is shown to be large enough, so that for any stationary process, almost all of its paths are in A. On the other hand, we prove that any path in A will behave in the optimal way under any stationarity test satisfying some mild conditions.

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Valera, Harold Glenn A., Mark J. Holmes, and Gazi M. Hassan. "Does inflation targeting matter for the behavior of inflation and output growth? Some regime-based evidence for Asian economies." Journal of Economic Studies 45, no. 5 (2018): 932–55. http://dx.doi.org/10.1108/jes-01-2017-0023.

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PurposeThe purpose of this paper is to consider whether or not the introduction of inflation targeting (IT) impacts on the mean-reversion properties of inflation and output growth.Design/methodology/approachFocusing on eight Asian countries of which four are inflation-targeters, the authors employ a two-state Markov-switching model which characterizes the behavior of inflation and output growth as regime-dependent based on periods of stationarity or non-stationarity.FindingsIn contrast to a literature that offers mixed findings, the authors find the presence of stationary inflation and output

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Česnik, Martin, Janko Slavič, Lorenzo Capponi, Massimiliano Palmieri, Filippo Cianetti, and Miha Boltežar. "The relevance of non-stationarities and non-Gaussianities in vibration fatigue." MATEC Web of Conferences 165 (2018): 10011. http://dx.doi.org/10.1051/matecconf/201816510011.

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In classical fatigue of materials, the frequency contents of dynamic loading are well below the natural frequencies of the observed structure or test specimen. However, when dealing with vibration fatigue the frequency contents of dynamic loading and structure's dynamic response overlap, resulting in amplified stress loads of the structure. For such cases, frequency counting methods are especially convenient. Gaussianity and stationarity assumptions are applied in frequency-domain methods for obtaining dynamic structure's response and frequency-domain methods for calculating damage accumulatio

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Lu, Zhiping, Ming Li, and Wei Zhao. "Stationarity Testing of Accumulated Ethernet Traffic." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/217213.

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We investigate the stationarity property of the accumulated Ethernet traffic series. We applied several widely used stationarity and unit root tests, such as Dickey-Fuller test and its augmented version, Phillips-Perron test, as well as the Kwiatkowski-Phillips-Schmidt-Shin test and some of its generalizations, to the assessment of the stationarity of the traffic traces at the different time scales. The quantitative results in this research provide evidence that when the time scale increases, the accumulated traffic series are more stationary.

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9

Tan, Yi, Jesper Ødum Nielsen, and Gert Frølund Pedersen. "Spatial Stationarity of Ultrawideband and Millimeter Wave Radio Channels." International Journal of Antennas and Propagation 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/3212864.

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For radio channels with broad bandwidth resource, such as those often used for ultrawideband (UWB) and millimeter wave (mmwave) systems, the Wide-Sense Stationary Uncorrelated Scattering (WSSUS) and spatial stationary assumptions are more critical than typical cellular channels with very limited bandwidth resource. This paper studies spatial stationarity and bandwidth dependency of the Multipath Component (MPC) parameters, and the concept of local region of stationarity (LRS) is used as the measure of the physical stationarity region. LRS calculation results based on channel measurements show

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10

Arrieta-Pastrana, Alfonso, Manuel Saba, and Adriana Puello Alcázar. "Analysis of Climate Variability in a Time Series of Precipitation and Temperature Data: A Case Study in Cartagena de Indias, Colombia." Water 14, no. 9 (2022): 1378. http://dx.doi.org/10.3390/w14091378.

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Anthropogenic climate change is a global trend, hitherto incontrovertible, causing immense social and economic damage. Although the this is evident at the global level, at the local level, there is still debate about the most appropriate analyses to support this fact. This debate is particularly relevant in developing countries, such as Colombia, where there is a significant lack of data at the local level that require analysis and interpretation. Consequently, studies are often superficially conducted to support climate change theory at the local level. However, such studies are then used to

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Arrieta-Pastrana, Alfonso, Manuel Saba, and Adriana Puello Alcázar. "Analysis of Climate Variability in a Time Series of Precipitation and Temperature Data: A Case Study in Cartagena de Indias, Colombia." Water 14, no. 9 (2022): 1378. http://dx.doi.org/10.3390/w14091378.

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Anthropogenic climate change is a global trend, hitherto incontrovertible, causing immense social and economic damage. Although the this is evident at the global level, at the local level, there is still debate about the most appropriate analyses to support this fact. This debate is particularly relevant in developing countries, such as Colombia, where there is a significant lack of data at the local level that require analysis and interpretation. Consequently, studies are often superficially conducted to support climate change theory at the local level. However, such studies are then used to

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12

Ren, Huiying, Z. Jason Hou, Mark Wigmosta, Ying Liu, and L. Ruby Leung. "Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed." Water 11, no. 6 (2019): 1296. http://dx.doi.org/10.3390/w11061296.

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Changes in extreme precipitation events may require revisions of civil engineering standards to prevent water infrastructures from performing below the designated guidelines. Climate change may invalidate the intensity-duration-frequency (IDF) computation that is based on the assumption of data stationarity. Efforts in evaluating non-stationarity in the annual maxima series are inadequate, mostly due to the lack of long data records and convenient methods for detecting trends in the higher moments. In this study, using downscaled high resolution climate simulations of the historical and future

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Wang, Zuo-Cai, Feng Wu, and Wei-Xin Ren. "Stationarity test of vibration signals with surrogate data and time–frequency analysis." Advances in Structural Engineering 20, no. 8 (2016): 1143–54. http://dx.doi.org/10.1177/1369433216677602.

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The stationarity test of vibration signals is critical for the extraction of the signal features. In this article, the surrogate data with various time–frequency analysis methods are proposed for stationary test of vibration signals. The surrogate data are first generated from the Fourier spectrum of the original signal with keeping the magnitude of the spectrum unchanged and replacing its phase by a random sequence. The local and global spectra of the original signal and the surrogate data are then estimated by four time–frequency analysis methods, which are short-time Fourier transform, mult

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14

Kalamkar, V. A. "Minification processes with discrete marginals." Journal of Applied Probability 32, no. 3 (1995): 692–706. http://dx.doi.org/10.2307/3215123.

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We investigate the stationarity of minification processes when the marginal is a discrete distribution. There is a close relationship between the problem considered by Arnold and Isaacson (1976) and the stationarity in minification processes. We give a necessary and sufficient condition for a discrete distribution to be the marginal of a stationary minification process. Members of the Poisson and negative binomial families can be the marginals of stationary minification processes. The geometric minification process is studied in detail, and two characterizations of it based on the structure of

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Kalamkar, V. A. "Minification processes with discrete marginals." Journal of Applied Probability 32, no. 03 (1995): 692–706. http://dx.doi.org/10.1017/s0021900200103146.

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We investigate the stationarity of minification processes when the marginal is a discrete distribution. There is a close relationship between the problem considered by Arnold and Isaacson (1976) and the stationarity in minification processes. We give a necessary and sufficient condition for a discrete distribution to be the marginal of a stationary minification process. Members of the Poisson and negative binomial families can be the marginals of stationary minification processes. The geometric minification process is studied in detail, and two characterizations of it based on the structure of

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Genton, Marc G., and Olivier Perrin. "On a time deformation reducing nonstationary stochastic processes to local stationarity." Journal of Applied Probability 41, no. 1 (2004): 236–49. http://dx.doi.org/10.1239/jap/1077134681.

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A stochastic process is locally stationary if its covariance function can be expressed as the product of a positive function multiplied by a stationary covariance. In this paper, we characterize nonstationary stochastic processes that can be reduced to local stationarity via a bijective deformation of the time index, and we give the form of this deformation under smoothness assumptions. This is an extension of the notion of stationary reducibility. We present several examples of nonstationary covariances that can be reduced to local stationarity. We also investigate the particular situation of

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Genton, Marc G., and Olivier Perrin. "On a time deformation reducing nonstationary stochastic processes to local stationarity." Journal of Applied Probability 41, no. 01 (2004): 236–49. http://dx.doi.org/10.1017/s0021900200014170.

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A stochastic process is locally stationary if its covariance function can be expressed as the product of a positive function multiplied by a stationary covariance. In this paper, we characterize nonstationary stochastic processes that can be reduced to local stationarity via a bijective deformation of the time index, and we give the form of this deformation under smoothness assumptions. This is an extension of the notion of stationary reducibility. We present several examples of nonstationary covariances that can be reduced to local stationarity. We also investigate the particular situation of

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18

Muhammadullah, Sara, Amena Urooj, and Faridoon Khan. "A revisit of the unemployment rate, interest rate, GDP growth and Inflation of Pakistan: Whether Structural break or unit root?" iRASD Journal of Economics 3, no. 2 (2021): 80–92. http://dx.doi.org/10.52131/joe.2021.0302.0027.

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The study investigates the query of structural break or unit root considering four macroeconomic indicators; unemployment rate, interest rate, GDP growth, and inflation rate of Pakistan. The previous studies create ambiguity regarding the stationarity and non-stationarity of these variables. We employ Zivot & Andrews (1992) unit root test and Step Indicator Saturation (SIS) method for multiple break detection in mean. GDP growth and inflation rate are stationary at level whereas unit root tests fail to reject the null hypothesis of the unemployment rate and interest rate at level. However,

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Benoit, Lionel, Mathieu Vrac, and Gregoire Mariethoz. "Dealing with non-stationarity in sub-daily stochastic rainfall models." Hydrology and Earth System Sciences 22, no. 11 (2018): 5919–33. http://dx.doi.org/10.5194/hess-22-5919-2018.

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Abstract. Understanding the stationarity properties of rainfall is critical when using stochastic weather generators. Rainfall stationarity means that the statistics being accounted for remain constant over a given period, which is required for both inferring model parameters and simulating synthetic rainfall. Despite its critical importance, the stationarity of precipitation statistics is often regarded as a subjective choice whose examination is left to the judgement of the modeller. It is therefore desirable to establish quantitative and objective criteria for defining stationary rain perio

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Puchstein, Ruprecht, and Philip Preuß. "Testing for Stationarity in Multivariate Locally Stationary Processes." Journal of Time Series Analysis 37, no. 1 (2015): 3–29. http://dx.doi.org/10.1111/jtsa.12133.

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Li, Fang, Wei Chen, and Yishui Shui. "Analysis of Non-Stationarity for 5.9 GHz Channel in Multiple Vehicle-to-Vehicle Scenarios." Sensors 21, no. 11 (2021): 3626. http://dx.doi.org/10.3390/s21113626.

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The vehicle-to-vehicle (V2V) radio channel is non-stationary due to the rapid movement of vehicles. However, the stationarity of the V2V channels is an important indicator of the V2V channel characteristics. Therefore, we analyzed the non-stationarity of V2V radio channels using the local region of stationarity (LRS). We selected seven scenarios, including three directions of travel, i.e., in the same, vertical, and opposite directions, and different speeds and environments in a similar driving direction. The power delay profile (PDP) and LRS were estimated from the measured channel impulse re

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Arellano, Consuelo, and Sastry G. Pantula. "TESTING FOR TREND STATIONARITY VERSUS DIFFERENCE STATIONARITY." Journal of Time Series Analysis 16, no. 2 (1995): 147–64. http://dx.doi.org/10.1111/j.1467-9892.1995.tb00227.x.

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Pareek, Vishakha, Santanu Chaudhury, and Sanjay Singh. "Handling non-stationarity in E-nose design: a review." Sensor Review 42, no. 1 (2021): 39–61. http://dx.doi.org/10.1108/sr-02-2021-0038.

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Purpose The electronic nose is an array of chemical or gas sensors and associated with a pattern-recognition framework competent in identifying and classifying odorant or non-odorant and simple or complex gases. Despite more than 30 years of research, the robust e-nose device is still limited. Most of the challenges towards reliable e-nose devices are associated with the non-stationary environment and non-stationary sensor behaviour. Data distribution of sensor array response evolves with time, referred to as non-stationarity. The purpose of this paper is to provide a comprehensive introductio

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Livadiotis, G., and D. J. McComas. "What Defines Stationarity in Space Plasmas." Astrophysical Journal 982, no. 2 (2025): 169. https://doi.org/10.3847/1538-4357/adb8d2.

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Abstract Starting from the concept of entropy defect in thermodynamics, we construct the entropy formulation of space plasmas, and then use it to develop a measure of their stationarity. In particular, we show that the statistics of this entropy results in two findings that improve our understanding of stationary and nonstationary systems: (i) variations of Boltzmann−Gibbs (BG) entropy do not exceed twice the value of the thermodynamic kappa, the parameter that provides a measure of the entropy defect in both stationary and nonstationary states, while becoming the shape parameter that labels t

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Mohd Lokoman, Rahmah, Fadhilah Yusof, Nor Eliza Alias, and Zulkifli Yusop. "Construction of Dependence Structure for Rainfall Stations by Joining Time Series Models with Copula Method." Malaysian Journal of Fundamental and Applied Sciences 17, no. 4 (2021): 306–20. http://dx.doi.org/10.11113/mjfas.v17n4.2345.

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Copula model has applied in various hydrologic studies, however, most analyses conducted does not considering the non-stationary conditions that may exist in the time series. To investigate the dependence structure between two rainfall stations at Johor Bahru, two methods have been applied. The first method considers the non-stationary condition that exists in the data, while the second method assumes stationarity in the time series data. Through goodness-off-fit (GOF) and simulation tests, performance of both methods are compared in this study. The results obtained in this study highlight the

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Yilmaz, Abdullah Gokhan, Monzur Alam Imteaz, Abdallah Shanableh, Rami Al-Ruzouq, Serter Atabay, and Khaled Haddad. "A Non-Stationarity Analysis of Annual Maximum Floods: A Case Study of Campaspe River Basin, Australia." Water 15, no. 20 (2023): 3683. http://dx.doi.org/10.3390/w15203683.

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A design flood is an essential input for water infrastructure design and flood protection. A flood frequency analysis has been traditionally performed under stationarity assumption indicating that the statistical properties of historical flooding will not change over time. Climate change and variability challenges the stationarity assumption, and a flood frequency analysis without consideration of non-stationarity can result in under- or overestimation of the design floods. In this study, non-stationarity of annual maximum floods (AMFs) was investigated through a methodology consisting of tren

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ISLIKER, HEINZ, and JÜRGEN KURTHS. "A TEST FOR STATIONARITY: FINDING PARTS IN TIME SERIES APT FOR CORRELATION DIMENSION ESTIMATES." International Journal of Bifurcation and Chaos 03, no. 06 (1993): 1573–79. http://dx.doi.org/10.1142/s0218127493001227.

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We propose a method to identify stationary phases in time series. Stationarity is a necessary condition for many concepts in dynamical systems theory, e.g. deterministic chaos. Therefore, testing for stationarity should necessarily be the first step in any data analysis. Above all, this testing is highly important whenever one deals with systems for which stationarity is not guaranteed by the data acquisition procedure: if only short and unique time series are accessible and if the experimental situation is not or only restrictedly controllable, as for instance in astronomy, economy, or medici

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Bette, Henrik M., Michael Schreckenberg, and Thomas Guhr. "Sensitivity of principal components to system changes in the presence of non-stationarity." Journal of Statistical Mechanics: Theory and Experiment 2023, no. 10 (2023): 103402. http://dx.doi.org/10.1088/1742-5468/ad0033.

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Abstract Non-stationarity affects the sensitivity of change detection in correlated systems described by sets of measurable variables. We study this by projecting onto different principal components. Non-stationarity is modeled as multiple normal states that exist in the system even before a change occurs. The studied changes occur in mean values, standard deviations or correlations of the variables. Monte Carlo simulations are performed to test the sensitivity for change detection with and without knowledge about non-stationarity for different system dimensions and numbers of normal states. A

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Marques, Julian M. E., Denis Benasciutti, Jan Papuga, and Milan Růžička. "Uncertainty of Estimated Rainflow Damage in Stationary Random Loadings and in Those Stationary per partes." Applied Sciences 13, no. 5 (2023): 2808. http://dx.doi.org/10.3390/app13052808.

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The uncertainty of rainflow fatigue damage is evaluated for stationary loadings and for non-stationary switching loadings with a finite number of stationary states. The approach is based on confidence intervals constructed after direct analysis of stress-time histories. The accuracy of confidence intervals is verified first by numerical simulations, and then by experimental data measured in a mountain bike traveling under various driving and road surface conditions, yielding stationary and non-stationary switching loadings. Stationarity and non-stationarity of loading records is checked by a s

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Conni, Michele, and Hilda Deborah. "Texture Stationarity Evaluation with Local Wavelet Spectrum." London Imaging Meeting 2020, no. 1 (2020): 24–27. http://dx.doi.org/10.2352/issn.2694-118x.2020.lim-20.

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In texture analysis, stationarity is a fundamental property. There are various ways to evaluate if a texture image is stationary or not. One of the most recent and effective of these is a standard test based on non-decimated stationary wavelet transform. This method permits to evaluate how stationary is an image depending on the scale considered. We propose to use this feature to characterize an image and we discuss the implication of such approach.

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Husein, Jamal, and S. Murat Kara. "Permanent VS Transitory Shocks to Electricity Consumption: Panel Evidence from 19 African Countries." Journal of Developing Areas 58, no. 2 (2024): 257–68. http://dx.doi.org/10.1353/jda.2024.a924539.

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ABSTRACT: Considering Africa's increasing electricity demands and the pivotal role of electricity in socio-economic development, this study addresses a research gap in understanding the stochastic properties of per capita electricity consumption in African contexts. Through examining the integration properties of per capita electricity consumption across 19 African countries, the research determines whether 'shocks' yield transitory or permanent effects, aiding policy formulation and future demand forecasting. Annual electric power consumption data (1971 – 2014) (kWh per capita) from the WDI a

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Guo, Zhichao. "Research on the Augmented Dickey-Fuller Test for Predicting Stock Prices and Returns." Advances in Economics, Management and Political Sciences 44, no. 1 (2023): 101–6. http://dx.doi.org/10.54254/2754-1169/44/20232198.

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With the continuous accumulation of theoretical knowledge and progressive applied research, analyzing financial time series data gradually becomes everlasting research in modern days. The simpler Dickey-Fuller originally is a test commonly used in econo-metrics and finance to test the stationarity of financial time series data. Thereafter, simpler Dickey-Fuller is eventually extended to the augmented Dickey-Fuller test to examine the stationarity of financial time series data such as stock prices, returns, and so on. This paper mainly focuses on the utilization of the augment Dickey-Fuller tes

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Abdullah, Shadab. "VALIDATING STATIONARITY AS AN ANTECEDENT TO STUDYING THE IMPACT OF EXCHANGE RATE VOLATILITY ON BANKEX VALUES." Indian Journal of Economics and Business 20, no. 2 (2021): 511–21. https://doi.org/10.5281/zenodo.5410699.

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Abstract: The time series data were experimented for Unit-Root. This test normally conducted to ascertain the time series stationarity and to agree on the array of assimilation of the variables. It is obligatory to conduct the Unit-Root test for the rationale that the trouble of variables with non-stationary producing spurious or meaningless effects due to the occurrence of trend in the data series. This testing procedure is completed by means of the Unit-Root testing methodology. In this paper stationarity assessed for the data collected for the purpose of studying the impact of exchange rate

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Yonghua, Mao. "Stationarity and quasi-stationarity for birth-death processes." SCIENTIA SINICA Mathematica 49, no. 3 (2019): 467. http://dx.doi.org/10.1360/n012018-00047.

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Tovstik, T. M. "Vector autoregression process. Stationarity and simulation." Journal of Physics: Conference Series 2099, no. 1 (2021): 012068. http://dx.doi.org/10.1088/1742-6596/2099/1/012068.

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Abstract For vector discrete-parameter random autoregressive processes and for a mixed autoregression/moving-average model, we obtain conditions which should be satisfied by the correlation functions or the model coefficients in order that the process be weakly stationary. Fairly simple tests are used. Algorithms for modeling such vector stationary processes are given. Examples are presented clarifying testing criteria for stationarity of models defned in terms of the coefficients or the correlation functions of the process.

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Last, Günter, and Hermann Thorisson. "Invariant transports of stationary random measures and mass-stationarity." Annals of Probability 37, no. 2 (2009): 790–813. http://dx.doi.org/10.1214/08-aop420.

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Shang, Shang, Kangning He, Zhaobin Wang, and Xuguang Yang. "Stationary Time Statistical Property of Ionospheric Clutter in High-Frequency Surface-Wave Radar." Journal of Electrical and Computer Engineering 2019 (November 3, 2019): 1–6. http://dx.doi.org/10.1155/2019/2450191.

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In HFSWR (high-frequency surface-wave radar) system, the detection performance is impacted seriously by ionospheric clutter. Frequency selection is an effective method to avoid the effect of ionospheric clutter. The key to the method is the stationarity of ionospheric clutter over a period of time. This paper mainly researches the stationary time statistical property of the ionospheric clutter. A large number of real data including ionospheric clutter in HFSWR are processed and analyzed. It shows that ionospheric clutter in HFSWR has the characteristics of approximate stationarity within a per

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Johnson, S. E., I. S. Ferguson, and Li Rong-wei. "Evaluation of a Stochastic Diameter Growth Model for Mountain Ash." Forest Science 37, no. 6 (1991): 1671–81. http://dx.doi.org/10.1093/forestscience/37.6.1671.

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Abstract A stationary Markov model of diameter growth in mountain ash (Eucalyptus regnans F. Muell.) was evaluated using remeasurement data collected over an 18-year period in a spacing trial located in south-central Victoria, Australia. The assumptions of Markovity and Stationarity central to this approach were tested using χ² statistics not previously employed in this context, The Stationarity assumption was found to be violated in this analysis, leading to the conclusion that alternative time and density dependent models should be pursued for this species. For. Sci. 37(6):1671-1681.

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Ma, Xiang, Xuemei Li, Lexin Fang, Tianlong Zhao, and Caiming Zhang. "U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 13 (2024): 14255–62. http://dx.doi.org/10.1609/aaai.v38i13.29337.

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Time series forecasting is a crucial task in various domains. Caused by factors such as trends, seasonality, or irregular fluctuations, time series often exhibits non-stationary. It obstructs stable feature propagation through deep layers, disrupts feature distributions, and complicates learning data distribution changes. As a result, many existing models struggle to capture the underlying patterns, leading to degraded forecasting performance. In this study, we tackle the challenge of non-stationarity in time series forecasting with our proposed framework called U-Mixer. By combining Unet and

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Rahimullaily, Rahimullaily, and Amalina Amalina. "Kestasioneran Kurs Dolar Amerika dan Harga Saham Pada Masa Pandemi Covid 19 Tahun 2020." JOSTECH: Journal of Science and Technology 1, no. 1 (2021): 83–91. http://dx.doi.org/10.15548/jostech.v1i1.2439.

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This study aims to determine the stationarity of the US dollar exchange rate and stock prices during the Covid 19 pandemic. One of the interesting stocks to study is the stock price of PT Telecommunications Indonesia Tbk. The augmented Dickey-Fuller test was used to determine the stationarity of the two variables. The research data is sourced from secondary data through the official website of Bank Indonesia to view the US Dollar Exchange Rate and through the website investing to see the stock price of PT. Telekomunikasi Indonesia Tbk during the Covid 19 pandemic period in Indonesia occurred f

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Wang, Hong, and Fubao Sun. "On the Stationarity of Annual Precipitation over China (1959–2018)." Journal of Hydrometeorology 21, no. 5 (2020): 881–90. http://dx.doi.org/10.1175/jhm-d-19-0195.1.

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AbstractStationarity is an assumption that permeates training and practice in water-resource engineering. However, with global change, the validity of stationarity as well as uncertainty of nonstationarity in water-resource planning are being questioned; thus, it is critical to evaluate the stationarity of climate variables, especially precipitation. Based on the continuous observation data of precipitation from 1427 stations across China, 593 efficient grid cells (1° × 1°) are constructed, and the annual precipitation stationarities from 1959 to 2018 are analyzed. The evaluated autocorrelatio

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Ribeiro, Maria Eduarda, Taison Anderson Bortolin, Ludmilson Abritta Mendes, and Leonardo de Carvalho Souza Santa Rita. "Análise de Séries Hidrológicas na Bacia Hidrográfica afluente à Usina Hidrelétrica Castro Alves, RS." Revista Brasileira de Geografia Física 14, no. 4 (2021): 2042–58. http://dx.doi.org/10.26848/rbgf.v14.4.p2042-2058.

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This study aims to analyze the stationariety and homogeneity of rainfall and streamflow series of the contribution basin of Castro Alves Hydroeletric Power Plant, in Southern Brazil. The rainfall data were acquired from the Agência Nacional de Águas, and the average rainfall series was calculated for the period from 1945 to 2017. The streamflow data were acquired from the Operador Nacional do Sistema Elétrico covering a period from 1945 to 2017. The analysis were performed in the complete series and in two periods obtained from the same, referring to the period before and after 1970. Six stati

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Li, Long-Fei, Peng Zhao, and Zhi-Hua Zhou. "Dynamic Regret of Adversarial MDPs with Unknown Transition and Linear Function Approximation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 12 (2024): 13572–80. http://dx.doi.org/10.1609/aaai.v38i12.29261.

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We study reinforcement learning (RL) in episodic MDPs with adversarial full-information losses and the unknown transition. Instead of the classical static regret, we adopt dynamic regret as the performance measure which benchmarks the learner's performance with changing policies, making it more suitable for non-stationary environments. The primary challenge is to handle the uncertainties of unknown transition and unknown non-stationarity of environments simultaneously. We propose a general framework to decouple the two sources of uncertainties and show the dynamic regret bound naturally decomp

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Fell, Jürgen, Alexander Kaplan, Boris Darkhovsky, and Joachim Röschke. "EEG analysis with nonlinear deterministic and stochastic methods: a combined strategy." Acta Neurobiologiae Experimentalis 60, no. 1 (2000): 87–108. http://dx.doi.org/10.55782/ane-2000-1328.

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We describe nonlinear deterministic versus stochastic methodology, their applications to EEG research and the neurophysiological background underlying both approaches. Nonlinear methods are based on the concept of attractors in phase space. This concept on the one hand incorporates the idea of an autonomous (stationary) system, on the other hand implicates the investigation of a long time evolution. It is an unresolved problem in nonlinear EEG research that nonlinear methods per se give no feedback about the stationarity aspect. Hence, we introduce a combined strategy utilizing both stochastic

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Rupassara, Upul, Sarah Frantsvog, Ashley Holen, and Karen Robinson. "Analysis of the stationarity and correlation of the global temperature and carbon dioxide time series." F1000Research 12 (August 31, 2023): 1074. http://dx.doi.org/10.12688/f1000research.139583.1.

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Background: The rapid and ongoing phenomenon of global warming has negatively impacted both the Earth’s environment and its inhabitants. Time series and regression analysis techniques play a significant role in weather forecasting and the interpretation of climate data. One of the key characteristics of time series analysis is stationarity. Methods: In this article, we explore how detrending and differencing techniques can be used to transform the time series of global temperature and carbon dioxide into stationary series. Regression models and goodness of fit tests were used to examine the re

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Wang, Muyao, Wenchao Chen, and Bo Chen. "Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 14 (2024): 15563–70. http://dx.doi.org/10.1609/aaai.v38i14.29483.

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The forecasting of Multivariate Time Series (MTS) has long been an important but challenging task. Due to the non-stationary problem across long-distance time steps, previous studies primarily adopt stationarization method to attenuate the non-stationary problem of original series for better predictability. However, existed methods always adopt the stationarized series, which ignore the inherent non-stationarity, and have difficulty in modeling MTS with complex distributions due to the lack of stochasticity. To tackle these problems, we first develop a powerful hierarchical probabilistic gener

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Ferreira, Isabela Arantes, Mariana Borges Albuquerque, Bruno Henrique Toná Juliani, Sandro Lautenschlager, Cristhiane Michiko Passos Okawa, and Antonio Carlos Zuffo. "Stationarity of pluviometric series of the state of Ceará, Brazil." Ciência e Natura 44 (April 20, 2022): e22. http://dx.doi.org/10.5902/2179460x68824.

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This paper aims to investigate stationarity in the pluviometric historical series of the state of Ceará, Brazil. After selection, the gaps were filled using linear regression. The Mann-Kendall and Pettitt tests were conducted with the help of the package “trend”, in R programming language. After applying the tests, it was noted that most of the selected stations presented stationary behavior, except for Chorozinho, which presented a p-value of 0,018 for the Mann-Kendall test, i.e., rejecting the null hypothesis of stationarity at 5% significance and presenting a positive monotone trend. For th

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HILFER, R. "FOUNDATIONS OF FRACTIONAL DYNAMICS." Fractals 03, no. 03 (1995): 549–56. http://dx.doi.org/10.1142/s0218348x95000485.

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Time flow in dynamical systems is reconsidered in the ultralong time limit. The ultralong time limit is a limit in which a discretized time flow is iterated infinitely often and the discretization time step is infinite. The new limit is used to study induced flows in ergodic theory, in particular for subsets of measure zero. Induced flows on subsets of measure zero require an infinite renormalization of time in the ultralong time limit. It is found that induced flows are given generically by stable convolution semigroups and not by the conventional translation groups. This could give new insig

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Oruc, Sertac. "Non-stationary Investigation of Extreme Rainfall." Civil Engineering Journal 7, no. 9 (2021): 1620–33. http://dx.doi.org/10.28991/cej-2021-03091748.

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Natural or human-induced variability emerged from investigation of the traditional stationary assumption regarding extreme precipitation analyses. The frequency of extreme rainfall occurrence is expected to increase in the future and neglecting these changes will result in the underestimation of extreme events. However, applications of extremes accept the stationarity that assumes no change over time. Thus, non-stationarity of extreme precipitation of 5, 10, 15, and 30 minutes and 1-, 3-, 6-, and 24-hour data of 17 station in the Black Sea region were investigated in this study. Using one stat

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Bossa, Aymar Yaovi, Jean de Dieu Akpaca, Jean Hounkpè, Yacouba Yira, and Djigbo Félicien Badou. "Non-Stationary Flood Discharge Frequency Analysis in West Africa." GeoHazards 4, no. 3 (2023): 316–27. http://dx.doi.org/10.3390/geohazards4030018.

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With climate change and intensification of the hydrological cycle, the stationarity of hydrological variables is becoming questionable, requiring appropriate flood assessment models. Frequency analysis is widely used for flood forecasting. This study aims to determine the most suitable models (stationary and non-stationary) for estimating the maximum flows observed at some stations spread across West Africa. A statistical analysis of the annual maximum flows in terms of homogeneity, stationarity, and independence was carried out through the Pettitt, modified Mann–Kendall, and Wald–Wolfowitz te

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