Retrieving valuable knowledge and statistical patterns from official data has a great potential in supporting strategic policy making. Data Mining (DM) techniques are well-known for providing flexible and efficient analytical tools for data processing. In this paper, we provide an introduction...

This paper seeks to evaluate the appropriateness of a variety of existing forecasting techniques (17 methods) at providing accurate, and statistically significant forecasts for gold price. We report the results from the 9 most competitive techniques. Special consideration is given to the ability...

Accurate forecasts of home sales can provide valuable information for not only, policy makers, but also financial institutions and real estate professionals. Given this, our analysis compares the ability of two different versions of Singular Spectrum Analysis (SSA) methods, namely Recurrent SSA...

This paper seeks to evaluate the appropriateness of a variety of existing forecasting techniques (17 methods) at providing accurate, and statistically significant forecasts for gold price. We report the results from the 9 most competitive techniques. Special consideration is given to the ability...

This paper applies several causality tests to analyze whether sunspot numbers (used as an approximate proxy for the solar activity) cause global temperatures, using monthly data covering the time period 1880:1-2013:9. Both parametric and non-parametric causality tests are performed, which...

In this paper, the performance of the Singular Spectrum Analysis (SSA) technique is assessed by applying it to 24 series measuring the monthly seasonally unadjusted industrial production for important sectors of the German, French and UK economies. The results are compared with those obtained...

The characteristic function of the folded normal distribution and its moment function are derived. The entropy of the folded normal distribution and the Kullback–Leibler from the normal and half normal distributions are approximated using Taylor series. The accuracy of the results are also...

The detection of long-range dependence in time series analysis is an important task to which this paper contributes by showing that whilst the theoretical definition of a long-memory (or long-range dependent) process is based on the autocorrelation function, it is not possible for long memory to...

It is shown that the sum of the sample autocorrelation function at lag h≥1 is always −12 for any stationary time series with arbitrary length T≥2 (Hassani, 2009 [1]). In this paper, the distribution of a set of the sample autocorrelation function using the properties of this quantity is...