Methods for determining the presence of periodic correlation based on the bootstrap methodology

This paper presents methods for detecting the period of non Gaussian PC processes. A new statistic for testing periodic correlation is proposed. It is based on the bootstrap procedure which is used to estimate confidence intervals of coherence statistic. This method is linked to that of Hurd and Gerr based on Goodman's tests so both methodologies are also compared. It is demonstrated that in some situations the new test appears to be better.Periodic correlation; Bootstrap; Spectral representation;

Periodic correlation vs. integration and cointegration (Okresowa korelacja a integracja i kointegracja)

In this paper we present a new approach to integration and cointegration. We show that a periodically correlated time series can be divided in a natural way into subseries that are integrated. Moreover, with high probability they are cointegrated. Therefore it is enough to show periodic correlation of the original series to conclude that the subseries are integrated. In the first part of the paper we present the main features of periodically correlated processes and a method of detecting periodic correlation. We illustrate it using a data set of spot electricity prices from the Nord Pool Power Exchange. In the next section we show that the subseries (one for each day of the week) exhibit integration as well as cointegration.Cointegration; Integration; PARMA model; Periodic correlation;

On detecting and modeling periodic correlation in financial data

For many economic problems standard statistical analysis, based on the notion of stationarity, is not adequate. These include modeling seasonal decisions of consumers, forecasting business cycles and - as we show in the present article - modeling wholesale power market prices. We apply standard methods and a novel spectral domain technique to conclude that electricity price returns exhibit periodic correlation with daily and weekly periods. As such they should be modeled with periodically correlated processes. We propose to apply periodic autoregression (PAR) models which are closely related to the standard instruments in econometric analysis - vector autoregression (VAR) models.periodic correlation, sample coherence, electricity price, periodic autoregression, vector autoregression

Quantile estimation of probability distributions for maximum daily precipitation and short time series of observational data for engineering design

Knowledge of the distribution quantiles of precipitation maximum amounts is required in many fields concerning engineering design or hydrological risk assessment. When the number of observation years is small, it is not possible to fit the probability distribution function to maximum values and to calculate quantiles. This paper presents a procedure for calculating the quantiles of the probability distribution of daily precipitation maximums over a year using stochastic convergence of distributions. The distribution series of random variables, defined based on the cut-off sample with the elimination of the smallest values, made it possible to determine the quantiles for times series of order α of the distribution. These values were approximated by a function from the exponential class and then extrapolated to obtain quantiles for the distribution of maxima. The resulting quantile estimates, for short time series, were corrected using the kurtosis of the data used for estimation, which leads to a very large error reduction

Comparison of daily flows simulated for the year 2060 on the Kaczawa River for various scenarios of climate change by simple time series analysis

In this paper a time series analysis for daily flow simulations according three climate change scenario for Kaczawa River a left side tributary of the Odra River in south-west Poland is presented. The flow sequences were simulated using the hydrological model MIKE SHE and the spatial SWGEN meteorological data generator. Meteorological data for the hydrological model were generated based on data from 24 meteorological stations and 35-year daily data from the Institute of Meteorology and Water Management of the National Research Institute (IMGW). Data were generated for future climate condition for 2060 according GISS Model E, HadCM3, and GFDL R15 scenarios as well for the present conditions. The year 2000 was used as a reference year. The results obtained on the basis of a simple time series analysis point to small changes in flows for current and simulated conditions for 2060 for the Kaczawa River

Ocena poczucia bezpieczeństwa I dobrostanu społeczności lokalnej oraz kierunków przywracania dobrobytu społecznego z wykorzystaniem rozwiązań naturalnych

Constant progress of urbanization and the shortage of greenspaces, may cause a poor sense of security, the feeling of alienation among urban residents, leading to low social cohesion, loss of the sense of wellbeing and intensify urban stress. This paper presents the first stage of research in which the perception of the local community’s everyday life quality in relation to the place of residence and the level of integration were examined. A questionnaire survey has been carried out in the target group. 96 questionnaires were collected, 9 questions in relation to 9 demographic data were subjected to statistical analysis. The aim of the entire research is to indicate whether and to what extent, the introduced nature-based solutions are able to improve sense of security and wellbeing in the local community. The chi-square test of independence and the Spearman's rank correlation coefficient were determined. The results have revealed poor sense of security and community wellbeing in a certain group of respondents. The authors also discuss the positive impact of urban greenery on the social wellbeing parameters and point out the necessity to include NBSs in the systemic directions, on the example of the Grow Green project in the City of Wroclaw.Nieustanny postęp urbanizacji i niedobór terenów zielonych mogą powodować słabe poczucie bezpieczeństwa, poczucie wyobcowania wśród mieszkańców miast, prowadzące do niskiej spójności społecznej, utraty dobrego samopoczucia i nasilania miejskiego stresu. W artykule przedstawiono pierwszy etap badań, w którym badano postrzeganie jakości życia codziennego społeczności lokalnej w odniesieniu do miejsca zamieszkania i poziomu integracji. W grupie docelowej przeprowadzono badanie ankietowe. Zebrano 96 ankiet, analizie statystycznej poddano 9 pytań w odniesieniu do 9 danych demograficznych. Celem całego badania jest wskazanie, czy i w jakim stopniu wprowadzone rozwiązania przyrodnicze są w stanie poprawić poczucie bezpieczeństwa i dobrostanu w społeczności lokalnej. Wyznaczono test niezależności chi-kwadrat oraz współczynnik korelacji rang Spearmana. Wyniki ujawniły słabe poczucie bezpieczeństwa i dobrostanu społeczności w pewnej grupie respondentów. Autorzy omawiają również pozytywny wpływ zieleni miejskiej na parametry dobrostanu społecznego oraz wskazują na konieczność włączenia NBS w kierunki systemowe na przykładzie projektu Grow Green we Wrocławiu