Standard deviation of recurrence times for piecewise linear transformations

Fredholm Determinant for Piecewise Linear Transformations

We call the number ξ the lower Lyapunov number. We will study Spec^) , the spectrum of P \BV> the restriction of P to the subspace BV of functions with bounded variation. The generating function of P is determined by the orbits of the division points of the partition, and the orbits are characterized by a finite dimensional matrix Φ(z) which is defined by a renewal equation (§ 3). Hence, we can...

The Analysis of Iran Cotton Producers’ Risk Degree Based on Non-Linear Mean-Standard Deviation Model

As regards decreasing cotton cultivation in Iran during these years, the degree of risk taken by a cotton cultivator in the agricultural part is important. The studies showed that the cotton crop yield during the past years did not have enough growth and the cotton cost product in the period of study cotton production costs, has increased. In this paper, the risk orientation of cotton cultivato...

Comparison of derivative-based methods by normalized standard deviation approach for edge detection of gravity anomalies

This paper describes the application of the so-called normalized standard deviation (NSTD) method to detect edges of gravity anomalies. Using derivative-based methods enhances the anomaly edges, leading to significant improvement of the interpretation of the geological features. There are many methods for enhancing the edges, most of which are high-pass filters based on the horizontal or vertic...

The implications of piecewise linear process of normal accruals

The present study investigates whether the basic assumption in the Jones model, which normal accruals are a linear function of change in sales, is empirically valid. It also discusses and addresses the implications of the assumption violation in the earnings management detection tests. The research employs a sample of 2832 observations of the annual information of firms listed in Tehran Stock E...

Piecewise Constant Controlled Linear Fuzzy Systems