Time Series Analysis: Forecasting and Control

Distribution of the Estimators for Autoregressive Time Series with a Unit Root

Dickey, D. A., & Fuller, W. A. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10482531 · Cited by 23,211

Unit root tests in panel data: asymptotic and finite-sample properties

Levin, A., Lin, C.-F., & James Chu, C.-S. (2002) · Journal of Econometrics · doi:10.1016/s0304-4076(01)00098-7 · Cited by 12,849

Early-warning signals for critical transitions

Scheffer, M., Bascompte, J., Brock, W. A., Brovkin, V., Carpenter, S. R., Dakos, V., Held, H., van Nes, E. H., Rietkerk, M., & Sugihara, G. (2009) · Nature · doi:10.1038/nature08227 · Cited by 4,854

Forecasting with artificial neural networks:

Zhang, G., Eddy Patuwo, B., & Y. Hu, M. (1998) · International Journal of Forecasting · doi:10.1016/s0169-2070(97)00044-7 · Cited by 4,229

Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog.

Pagani, M., Lombardi, F., Guzzetti, S., Rimoldi, O., Furlan, R., Pizzinelli, P., Sandrone, G., Malfatto, G., Dell'Orto, S., & Piccaluga, E. (1986) · Circulation Research · doi:10.1161/01.res.59.2.178 · Cited by 4,130

Detection of Abrupt Changes: Theory and Application

Riedel, K. S. (1994) · Technometrics · doi:10.1080/00401706.1994.10485821 · Cited by 3,518

Political Parties and Macroeconomic Policy

Hibbs, D. A. (1977) · American Political Science Review · doi:10.1017/s0003055400269712 · Cited by 3,368

A review on lithium-ion battery ageing mechanisms and estimations for automotive applications

Barré, A., Deguilhem, B., Grolleau, S., Gérard, M., Suard, F., & Riu, D. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.05.040 · Cited by 1,758

Testing for causality

Granger, C. W. J. (1980) · Journal of Economic Dynamics and Control · doi:10.1016/0165-1889(80)90069-x · Cited by 1,746

Statistical and machine learning forecasting methods: Concerns and ways forward

Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2018) · PLOS ONE · doi:10.1371/journal.pone.0194889 · Cited by 1,528

Graph based anomaly detection and description: a survey

Akoglu, L., Tong, H., & Koutra, D. (2015) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-014-0365-y · Cited by 1,504

Combining nonoverlap and trend for single-case research: Tau-U

Parker, R. I., Vannest, K. J., Davis, J. L., & Sauber, S. B. (2011) · Behavior Therapy · doi:10.1016/j.beth.2010.08.006 · Cited by 1,468

Toward a modern theory of adaptive networks: Expectation and prediction.

Sutton, R. S., & Barto, A. G. (1981) · Psychological Review · doi:10.1037/0033-295x.88.2.135 · Cited by 1,450

Recurrent Neural Networks for Time Series Forecasting: Current status and future directions

Hewamalage, H., Bergmeir, C., & Bandara, K. (2021) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2020.06.008 · Cited by 1,371

Recurrent neural networks and robust time series prediction

Connor, J. T., Martin, R. D., & Atlas, L. E. (1994) · IEEE Transactions on Neural Networks · doi:10.1109/72.279188 · Cited by 1,316

A Comparison of ARIMA and LSTM in Forecasting Time Series

Siami-Namini, S., Tavakoli, N., & Siami Namin, A. (2018) · 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA) · doi:10.1109/icmla.2018.00227 · Cited by 1,387

Conducting Interrupted Time-series Analysis for Single- and Multiple-group Comparisons

Linden, A. (2015) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x1501500208 · Cited by 1,233

Model uncertainty, data mining and statistical inference

Chatfield, C. (1995) · Journal of the Royal Statistical Society. Series A (Statistics in Society) · doi:10.2307/2983440 · Cited by 1,103

North American drought: Reconstructions, causes, and consequences

Cook, E. R., Seager, R., Cane, M. A., & Stahle, D. W. (2007) · Earth-Science Reviews · doi:10.1016/j.earscirev.2006.12.002 · Cited by 862

Assessing the impact of planned social change

Campbell, D. T. (1979) · Evaluation and Program Planning · doi:10.1016/0149-7189(79)90048-x · Cited by 957

TS2Vec: Towards Universal Representation of Time Series

Yue, Z., Wang, Y., Duan, J., Yang, T., Huang, C., Tong, Y., & Xu, B. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i8.20881 · Cited by 850

Spectral Analysis of Blood Pressure and Heart Rate Variability in Evaluating Cardiovascular Regulation: A Critical Appraisal

Parati, G., Saul, J. P., Di Rienzo, M., & Mancia, G. (1995) · Hypertension · doi:10.1161/01.hyp.25.6.1276 · Cited by 849

Single-case experimental designs: a systematic review of published research and current standards

Smith, J. D. (2012) · Psychological Methods · doi:10.1037/a0029312 · Cited by 630

Modeling Multiple Time Series with Applications

Tiao, G. C., & Box, G. E. P. (1981) · Journal of the American Statistical Association · doi:10.1080/01621459.1981.10477728 · Cited by 626

Consequences of violating the independence assumption in analysis of variance.

Kenny, D. A., & Judd, C. M. (1986) · Psychological Bulletin · doi:10.1037/0033-2909.99.3.422 · Cited by 616

Handbook of frequency stability analysis

Riley, W. J., & Riley, W. J. (2008) · doi:10.6028/nist.sp.1065 · Cited by 586

Worldwide large-scale fluctuations of sardine and anchovy populations

Schwartzlose, R. A., Alheit, J., Bakun, A., Baumgartner, T. R., Cloete, R., Crawford, R. J. M., Fletcher, W. J., Green-Ruiz, Y., Hagen, E., Kawasaki, T., et al. (1999) · South African Journal of Marine Science · doi:10.2989/025776199784125962 · Cited by 548

DYNAMIC RESPONSE-BY-RESPONSE MODELS OF MATCHING BEHAVIOR IN RHESUS MONKEYS

Lau, B., & Glimcher, P. W. (2005) · Journal of the Experimental Analysis of Behavior · doi:10.1901/jeab.2005.110-04 · Cited by 485

How Unregulated Is the U.S. Labor Market? The Penal System as a Labor Market Institution

Western, B., & Beckett, K. (1999) · American Journal of Sociology · doi:10.1086/210135 · Cited by 489

Characterization of the physiological pattern of episodic gonadotropin secretion throughout the human menstrual cycle

FILICORI, M., SANTORO, N., MERRIAM, G. R., & CROWLEY, W. F. (1986) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jcem-62-6-1136 · Cited by 489

EMG feature evaluation for movement control of upper extremity prostheses

Zardoshti-Kermani, M., Wheeler, B. C., Badie, K., & Hashemi, R. M. (1995) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.481972 · Cited by 477

Heart Rate Turbulence: Standards of Measurement, Physiological Interpretation, and Clinical Use

Bauer, A., Malik, M., Schmidt, G., Barthel, P., Bonnemeier, H., Cygankiewicz, I., Guzik, P., Lombardi, F., Müller, A., Oto, A., et al. (2008) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2008.07.041 · Cited by 462

Global biomass burning: a synthesis and review of Holocene paleofire records and their controls

Marlon, J. R., Bartlein, P. J., Daniau, A.-L., Harrison, S. P., Maezumi, S. Y., Power, M. J., Tinner, W., & Vanniére, B. (2013) · Quaternary Science Reviews · doi:10.1016/j.quascirev.2012.11.029 · Cited by 438

Autoregressive Latent Trajectory (ALT) Models A Synthesis of Two Traditions

Bollen, K. A., & Curran, P. J. (2004) · Sociological Methods & Research · doi:10.1177/0049124103260222 · Cited by 447

Revealing the dynamic network structure of the Beck Depression Inventory-II

Bringmann, L. F., Lemmens, L. H. J. M., Huibers, M. J. H., Borsboom, D., & Tuerlinckx, F. (2015) · Psychological Medicine · doi:10.1017/s0033291714001809 · Cited by 371

Predicting ecosystem stability from community composition and biodiversity

de Mazancourt, C., Isbell, F., Larocque, A., Berendse, F., De Luca, E., Grace, J. B., Haegeman, B., Wayne Polley, H., Roscher, C., Schmid, B., et al. (2013) · Ecology Letters · doi:10.1111/ele.12088 · Cited by 382

Transcription-coupled changes in nuclear mobility of mammalian cis-regulatory elements

Gu, B., Swigut, T., Spencley, A., Bauer, M. R., Chung, M., Meyer, T., & Wysocka, J. (2018) · Science · doi:10.1126/science.aao3136 · Cited by 363

Treatment of Gad: Targeting Intolerance of Uncertainty in Two Types of Worry

Dugas, M. J., & Ladouceur, R. (2000) · Behavior Modification · doi:10.1177/0145445500245002 · Cited by 334

Spatial Analysis of Field Experiments-An Extension to Two Dimensions

Cullis, B. R., & Gleeson, A. C. (1991) · Biometrics · doi:10.2307/2532398 · Cited by 325

Increasing trends in high-severity fire in the southwestern USA from 1984 to 2015

Singleton, M. P., Thode, A. E., Sánchez Meador, A. J., & Iniguez, J. M. (2019) · Forest Ecology and Management · doi:10.1016/j.foreco.2018.11.039 · Cited by 291

Teaching about Approximate Confidence Regions Based on Maximum Likelihood Estimation

Meeker, W. Q., & Escobar, L. A. (1995) · The American Statistician · doi:10.1080/00031305.1995.10476112 · Cited by 279

Time Series Analysis Using Autoregressive Integrated Moving Average (ARIMA) Models

Nelson, B. K. (1998) · Academic Emergency Medicine · doi:10.1111/j.1553-2712.1998.tb02493.x · Cited by 262

The Lost Colony and Jamestown Droughts

Stahle, D. W., Cleaveland, M. K., Blanton, D. B., Therrell, M. D., & Gay, D. A. (1998) · Science · doi:10.1126/science.280.5363.564 · Cited by 267

Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

Yaseen, Z. M., Ebtehaj, I., Bonakdari, H., Deo, R. C., Danandeh Mehr, A., Mohtar, W. H. M. W., Diop, L., El-shafie, A., & Singh, V. P. (2017) · Journal of Hydrology · doi:10.1016/j.jhydrol.2017.09.007 · Cited by 267

Black-White Inequalities in Mortality and Life Expectancy, 1933–1999: Implications for Healthy People 2010

Levine, R. S., Foster, J. E., Fullilove, R. E., Fullilove, M. T., Briggs, N. C., Hull, P. C., Husaini, B. A., & Hennekens, C. H. (2001) · Public Health Reports® · doi:10.1093/phr/116.5.474 · Cited by 262

Covariance between psychological and endocrine responses to pharmacological challenge and psychosocial stress: a question of timing

Schlotz, W., Kumsta, R., Layes, I., Entringer, S., Jones, A., & Wüst, S. (2008) · Psychosomatic Medicine · doi:10.1097/psy.0b013e3181810658 · Cited by 237

Forest fire causes and extent on United States Forest Service lands

Stephens, S. L. (2005) · International Journal of Wildland Fire · doi:10.1071/wf04006 · Cited by 232

Verifying the Solution from a Nonlinear Solver: A Case Study

McCullough, B. D., & Vinod, H. D. (2003) · American Economic Review · doi:10.1257/000282803322157133 · Cited by 220

The Single-Case Reporting Guideline In BEhavioural Interventions (SCRIBE) 2016: Explanation and elaboration.

Tate, R. L., Perdices, M., Rosenkoetter, U., McDonald, S., Togher, L., Shadish, W., Horner, R., Kratochwill, T., Barlow, D. H., Kazdin, A., et al. (2016) · Archives of Scientific Psychology · doi:10.1037/arc0000027 · Cited by 219

The Relationship Between Visual Analysis and Five Statistical Analyses in a Simple AB Single-Case Research Design

Brossart, D. F., Parker, R. I., Olson, E. A., & Mahadevan, L. (2006) · Behavior Modification · doi:10.1177/0145445503261167 · Cited by 217

Generative Semi-supervised Learning for Multivariate Time Series Imputation

Miao, X., Wu, Y., Wang, J., Gao, Y., Mao, X., & Yin, J. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i10.17086 · Cited by 210

A neural network ensemble method with jittered training data for time series forecasting

Zhang, G. P. (2007) · Information Sciences · doi:10.1016/j.ins.2007.06.015 · Cited by 196

Intra-individual variability in ADHD, autism spectrum disorders and Tourette's syndrome

Geurts, H. M., Grasman, R. P. P. P., Verté, S., Oosterlaan, J., Roeyers, H., van Kammen, S. M., & Sergeant, J. A. (2008) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2008.06.013 · Cited by 192

Human Activity and Rest In Situ

Roenneberg, T., Keller, L. K., Fischer, D., Matera, J. L., Vetter, C., & Winnebeck, E. C. (2015) · Methods in Enzymology · doi:10.1016/bs.mie.2014.11.028 · Cited by 175

The Impact of Empirical Accuracy Studies on Time Series Analysis and Forecasting

Fildes, R., & Makridakis, S. (1995) · International Statistical Review / Revue Internationale de Statistique · doi:10.2307/1403481 · Cited by 172

Single-subject designs as a tool for evidence-based clinical practice: Are they unrecognised and undervalued?

Perdices, M., & Tate, R. L. (2009) · Neuropsychological Rehabilitation · doi:10.1080/09602010903040691 · Cited by 170

Improved amino acid flexibility parameters

Smith, D. K., Radivojac, P., Obradovic, Z., Dunker, A. K., & Zhu, G. (2003) · Protein Science · doi:10.1110/ps.0236203 · Cited by 164

Firearm purchasing and firearm violence during the coronavirus pandemic in the United States: a cross-sectional study

Schleimer, J. P., McCort, C. D., Shev, A. B., Pear, V. A., Tomsich, E., De Biasi, A., Buggs, S., Laqueur, H. S., & Wintemute, G. J. (2021) · Injury Epidemiology · doi:10.1186/s40621-021-00339-5 · Cited by 179

Statistics For Correlated Data: Phylogenies, Space, And Time

Ives, A. R., & Zhu, J. (2006) · Ecological Applications · doi:10.1890/04-0702 · Cited by 147

Criminalizing Delinquency: The Deterrent Effects of the New York Juvenile Offender Law

Singer, S. I., & McDowall, D. (1988) · Law & Society Review · doi:10.2307/3053628 · Cited by 144

Fishing effects and life history traits: a case study comparing tropical versus temperate tunas

Fromentin, J.-M., & Fonteneau, A. (2001) · Fisheries Research · doi:10.1016/s0165-7836(00)00299-x · Cited by 144

Climatic Variables and Transmission of Malaria: A 12-Year Data Analysis in Shuchen County, China

Bi, P., Tong, S., Donald, K., Parton, K. A., & Ni, J. (2003) · Public Health Reports · doi:10.1016/s0033-3549(04)50218-2 · Cited by 141

A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China

Wang, S., Yu, L., Tang, L., & Wang, S. (2011) · Energy · doi:10.1016/j.energy.2011.09.010 · Cited by 135

A hybrid method based on wavelet, ANN and ARIMA model for short-term load forecasting

Fard, A. K., & Akbari-Zadeh, M.-R. (2014) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/0952813x.2013.813976 · Cited by 134

Reducing Gang Violence Using Focused Deterrence: Evaluating the Cincinnati Initiative to Reduce Violence (CIRV)

Engel, R. S., Tillyer, M. S., & Corsaro, N. (2013) · Justice Quarterly · doi:10.1080/07418825.2011.619559 · Cited by 124

Sharing and synchrony of behavior states and heart rate in nondepressed versus depressed mother-infant interactions

Field, T., Healy, B., & LeBlanc, W. G. (1989) · Infant Behavior and Development · doi:10.1016/0163-6383(89)90044-1 · Cited by 115

The temporal relationship between per capita alcohol consumption and harm: A systematic review of time lag specifications in aggregate time series analyses

Holmes, J., Meier, P. S., Booth, A., Guo, Y., & Brennan, A. (2012) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2011.12.005 · Cited by 112

Police Officers on Drug Corners in Philadelphia, Drug Crime, and Violent Crime: Intended, Diffusion, and Displacement Impacts

Lawton, B. A., Taylor, R. B., & Luongo, A. J. (2005) · Justice Quarterly · doi:10.1080/07418820500364619 · Cited by 115

School Life and Adolescents' Self-Esteem Trajectories

Morin, A. J. S., Maïano, C., Marsh, H. W., Nagengast, B., & Janosz, M. (2013) · Child Development · doi:10.1111/cdev.12089 · Cited by 112

The Methodological Progress of Tourism Demand Forecasting: A Review of Related Literature

Goh, C., & Law, R. (2011) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2011.562856 · Cited by 112

Circadian and ultradian rhythms of free glucocorticoid hormone are highly synchronized between the blood, the subcutaneous tissue, and the brain

Qian, X., Droste, S. K., Lightman, S. L., Reul, J. M. H. M., & Linthorst, A. C. E. (2012) · Endocrinology · doi:10.1210/en.2012-1484 · Cited by 110

Social vulnerability to climate in the "Little Ice Age": an example from Central Europe in the early 1770s

Pfister, C., & Brázdil, R. (2006) · Climate of the Past · doi:10.5194/cp-2-115-2006 · Cited by 111

Catchment-scale hydrologic implications of parcel-level stormwater management (Ohio USA)

Shuster, W., & Rhea, L. (2013) · Journal of Hydrology · doi:10.1016/j.jhydrol.2012.10.043 · Cited by 104

Seasonal associations between weather conditions and suicide – evidence against a classic hypothesis

Ajdacic-Gross, V., Lauber, C., Sansossio, R., Bopp, M., Eich, D., Gostynski, M., Gutzwiller, F., & Rossler, W. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwk034 · Cited by 103

Neural network approach to forecasting of quasiperiodic financial time series

Bodyanskiy, Y., & Popov, S. (2006) · European Journal of Operational Research · doi:10.1016/j.ejor.2005.02.012 · Cited by 100

Post-traumatic stress disorder: a right temporal lobe syndrome?

Engdahl, B., Leuthold, A. C., Tan, H.-R. M., Lewis, S. M., Winskowski, A. M., Dikel, T. N., & Georgopoulos, A. P. (2010) · Journal of Neural Engineering · doi:10.1088/1741-2560/7/6/066005 · Cited by 97

Randomization tests for single-case experiments: State of the art, state of the science, and state of the application

Heyvaert, M., & Onghena, P. (2014) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2013.10.002 · Cited by 98

The use of time-series models and methods in the analysis of agricultural field trials

Martin, R. J. (1990) · Communications in Statistics - Theory and Methods · doi:10.1080/03610929008830187 · Cited by 95

Impact of UK policy initiatives on use of medicines to aid smoking cessation

West, R., DiMarino, M. E., Gitchell, J., & McNeill, A. (2005) · Tobacco Control · doi:10.1136/tc.2004.008649 · Cited by 92

Enhanced diagnostics for the spatial analysis of field trials

Stefanova, K. T., Smith, A. B., & Cullis, B. R. (2009) · Journal of Agricultural, Biological, and Environmental Statistics · doi:10.1198/jabes.2009.07098 · Cited by 88

The Aggregation of single-case results using hierarchical linear models

Van den Noortgate, W., & Onghena, P. (2007) · The Behavior Analyst Today · doi:10.1037/h0100613 · Cited by 86

Recurrent and Dynamic Models for Predicting Streaming Video Quality of Experience

Bampis, C. G., Li, Z., Katsavounidis, I., & Bovik, A. C. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2815842 · Cited by 84

Sex hormones and mental rotation: an intensive longitudinal investigation.

Courvoisier, D. S., Renaud, O., Geiser, C., Paschke, K., Gaudy, K., & Jordan, K. (2013) · Hormones and Behavior · doi:10.1016/j.yhbeh.2012.12.007 · Cited by 82

Increasing malaria hospital admissions in Uganda between 1999 and 2009

Okiro, E. A., Bitira, D., Mbabazi, G., Mpimbaza, A., Alegana, V. A., Talisuna, A. O., & Snow, R. W. (2011) · BMC Medicine · doi:10.1186/1741-7015-9-37 · Cited by 79

Alcohol and suicide in eastern Europe

LANDBERG, J. (2008) · Drug and Alcohol Review · doi:10.1080/09595230802093778 · Cited by 77

Traffic prediction using neural networks

Yu, E. S., & Chen, C. Y. R. (2002) · Proceedings of GLOBECOM '93. IEEE Global Telecommunications Conference · doi:10.1109/glocom.1993.318226 · Cited by 77

Effect of 11 September 2001 terrorist attacks in the USA on suicide in areas surrounding the crash sites

Claassen, C. A., Carmody, T., Stewart, S. M., Bossarte, R. M., Larkin, G. L., Woodward, W. A., & Trivedi, M. H. (2010) · British Journal of Psychiatry · doi:10.1192/bjp.bp.109.071928 · Cited by 74

Internet Traffic Forecasting using Neural Networks

Cortez, P., Rio, M., Rocha, M., & Sousa, P. (2006) · The 2006 IEEE International Joint Conference on Neural Network Proceedings · doi:10.1109/ijcnn.2006.247142 · Cited by 118

Untitled work

(2006) · Social Evolution & History · Cited by 73

Time Series Prediction Algorithm for Intelligent Predictive Maintenance

Lin, C.-Y., Hsieh, Y.-M., Cheng, F.-T., Huang, H.-C., & Adnan, M. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2918684 · Cited by 72

Environmental Reviews and Case Studies: Building Green Infrastructure via Citizen Participation: A Six-Year Study in the Shepherd Creek (Ohio)

Mayer, A. L., Shuster, W. D., Beaulieu, J. J., Hopton, M. E., Rhea, L. K., Roy, A. H., & Thurston, H. W. (2012) · Environmental Practice · doi:10.1017/s1466046611000494 · Cited by 72

Temporal relationship between dysfunctional beliefs, self-efficacy and panic apprehension in the treatment of panic disorder with agoraphobia

Bouchard, S., Gauthier, J., Nouwen, A., Ivers, H., Vallières, A., Simard, S., & Fournier, T. (2007) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/j.jbtep.2006.08.002 · Cited by 67

Bayesian Multilevel Analysis and MCMC

Draper, D. (2007) · Handbook of Multilevel Analysis · doi:10.1007/978-0-387-73186-5_2 · Cited by 69

Evidence for the effect of homes on wildfire suppression costs

Gude, P. H., Jones, K., Rasker, R., & Greenwood, M. C. (2013) · International Journal of Wildland Fire · doi:10.1071/wf11095 · Cited by 69

Forecasting life expectancy in an international context

Torri, T., & Vaupel, J. W. (2012) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2011.01.009 · Cited by 69

The effects of gainsharing on grievance rates and absenteeism over time

Arthur, J. B., & Jelf, G. S. (1999) · Journal of Labor Research · doi:10.1007/s12122-999-1029-3 · Cited by 66

Analysis of Variety Yield Trials Using Two-Dimensional Separable ARIMA Processes

Grondona, M. O., Crossa, J., Fox, P. N., & Pfeiffer, W. H. (1996) · Biometrics · doi:10.2307/2532916 · Cited by 66

Testing for deterministic trend and seasonal components in time series models

FRANZINI, L., & HARVEY, A. C. (1983) · Biometrika · doi:10.1093/biomet/70.3.673 · Cited by 66

Effects of Group Practice of the Transcendental Meditation Program on Preventing Violent Crime in Washington, D.C.: Results of the National Demonstration Project, June--July 1993

Hagelin, J. S., Rainforth, M. V., Cavanaugh, K. L. C., Alexander, C. N., Shatkin, S. F., Davies, J. L., Hughes, A. O., Ross, E., & Orme-Johnson, D. W. (1999) · Social Indicators Research · doi:10.1023/a:1006978911496 · Cited by 65