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The effect of long-term correlations on the return periods of rare events
Bunde, Armin; F. Eichner, Jan; Havlin, Shlomo; … - In: Physica A: Statistical Mechanics and its Applications 330 (2003) 1, pp. 1-7
The basic assumption of common extreme value statistics is that different events in a time record are uncorrelated. In this case, the return intervals rq of events above a given threshold size q are uncorrelated and follow the Poisson distribution. In recent years there is growing evidence that...
Persistent link: https://www.econbiz.de/10011063336
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Appropriateness of correlated first-order auto-regressive processes for modeling daily temperature records
Nagarajan, Radhakrishnan; Govindan, R.B. - In: Physica A: Statistical Mechanics and its Applications 364 (2006) C, pp. 271-275
The present study investigates linear and volatile (nonlinear) correlations of first-order auto-regressive process with uncorrelated AR (1) and long-range correlated CAR (1) Gaussian innovations as a function of the process parameter (θ). In the light of recent findings [A. Király, I.M....
Persistent link: https://www.econbiz.de/10011063484
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Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods
Kantelhardt, Jan W.; Rybski, Diego; Zschiegner, Stephan A. - In: Physica A: Statistical Mechanics and its Applications 330 (2003) 1, pp. 240-245
We study the multifractal temporal scaling properties of river discharge and precipitation records. We compare the results for the multifractal detrended fluctuation analysis method with the results for the wavelet-transform modulus maxima technique and obtain agreement within the error margins....
Persistent link: https://www.econbiz.de/10010588560
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Predicting in shock : on the impact of negative, extreme, rare, and short lived events on judgmental forecasts
Durbach, Ian; Montibeller, Gilberto - In: EURO Journal on decision processes 6 (2018) 1/2, pp. 213-233
Persistent link: https://www.econbiz.de/10011889486
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Mathematical programming formulations and algorithms for discrete k-median clustering of time-series data
Seref, Onur; Fan, Ya-ju; Chaovalitwongse, Wanpracha - In: INFORMS journal on computing : JOC 26 (2014) 1, pp. 160-172
Persistent link: https://www.econbiz.de/10010344112
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Machine learning treasury yields
Kakushadze, Zura; Yu, Willie - In: Bulletin of applied economics 7 (2020) 1, pp. 1-65
Persistent link: https://www.econbiz.de/10012807008
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Clustering life trajectories: A new divisive hierarchical clustering algorithm for discrete-valued discrete time series
Dlugosz, Stephan - 2011
A new algorithm for clustering life course trajectories is presented and tested with large register data. Life courses … clustering result for this kind of data provides interesting subgroups with similar life course trajectories. The high sampling … information. The new algorithm deals with this problem by simultaneously clustering and identifying critical junctures for each of …
Persistent link: https://www.econbiz.de/10010304330
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Estimating the drift time for processes subject to linear trend disturbance using fuzzy statistical clustering
Kazemi, Mohammad Sadegh; Bazargan, Hamid; Yaghoobi, … - In: International journal of production research 52 (2014) 11, pp. 3317-3330
Persistent link: https://www.econbiz.de/10010355756
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Cash demand forecasting in ATMs by clustering and neural networks
Venkatesh, Kamini; Ravi, Vadlamani; Prinzie, Anita; Van … - In: European journal of operational research : EJOR 232 (2014) 2, pp. 383-392
Persistent link: https://www.econbiz.de/10010224693
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Formation of seasonal groups and application of seasonal indices
Boylan, John E.; Chen, H.; Mohammadipour, M.; Syntetos, A. - In: Journal of the Operational Research Society : OR 65 (2014) 2, pp. 227-241
Persistent link: https://www.econbiz.de/10010239945