A stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk a

Through recent years many researchers have developed methods to estimate the self-similarity and long memory parameter that is best known as the Hurst parameter. In this paper, we set a comparison between nine different methods. Most of them use the deviations slope to find an estimate for the Hurst parameter like Rescaled range (R/S), Aggregate Variance (AV), and Absolute moments (AM), and some depend on filtration technique like Discrete Variations (DV), Variance versus level using wavelets (VVL) and Second-order discrete derivative using wavelets (SODDW) were the comparison set by a simulation study to find the most efficient method through MASE. The results of simulation experiments were shown that the performance of the meth

In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

A field study was conducted at the college of Agriculture, Baghdad University-Jadiriyah to investigate the effect of adding potassium fertilizer and organic nutrient (Reef Amirich) on the population density of two sucking pests of cucumber, cotton whitefly, Bemisia tabaci and onion thrips, Thrips tabaci during the spring season/2016. Results indicated that potassium sulphate (50, 100 and 150 kg/ha) and organic nutrient (0.8 and 1.6ml/l) reduced both the population density of B. tabaci and T. tabaci nymphs depending on the fertilizer level of the user, the treatment 150 kg/ha for the potassium fertilizer and 1.6 ml/L for organic nutrient was the highest among others when minimized density of nymphs by 1.62 nymphs of B. tabaci/disk leaf and 0

   The species Bostrichus capucinus  (L.) (Coleoptera:Bostrichidae) was reported as a new record for Iraq. Diagnostic characters and some information are given .

The present study included the collection of fresh samples of species of genus Oxalis and examined the anatomical characteristics of the stem, scape, petiole, leaf and pedicel

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals