SUMMARYThe paper presents new characterizations of the integer-valued moving average model. For four model variants, we give moments and probability generating functions. Yule}Walker and conditional least-squares estimators are obtained and studied by Monte Carlo simulation. A new generalized method of moment estimator based on probability generating functions is presented and shown to be consistent and asymptotically normal. The small sample performance is in some instances better than those of alternative estimators.
The Integer-valued Moving Average Model (INMA) is advanced to model the number of transactions in intra-day data of stocks. The conditional mean and variance properties are discussed and model extensions to include explanatory variables are offered. Least squares and generalized method of moment estimators are presented. In a small Monte Carlo study a feasible least squares estimator comes out as the best choice. Empirically we find support for the use of long-lag moving average models in a Swedish stock series. There is evidence of asymmetric effects of news about prices on the number of transactions.
The integer-valued AR1 model is generalized to encompass some of the more likely features of economic time series of count data. The generalizations come at the price of loosing exact distributional properties. For most specifications the first and second order both conditional and unconditional moments can be obtained. Hence estimation, testing and forecasting are feasible and can be based on least squares or GMM techniques. An illustration based on the number of plants within an industrial sector is considered.Characterization, Dependence, Time series model, Estimation, Forecasting, Entry and exit, JEL Classification: C12, C13, C22, C25, C51,
Use of the passive integrated transponder (PIT) as a fish identification and monitoring system for behavioral study of Arctic char Salvelinus alpinus was evaluated. The system was developed in order to track individual differences, mainly in rheotactic behavior. In a preliminary experimental setup, Arctic char (N = 20, 9–140 g each) were PIT‐tagged and their movements were recorded at regular intervals in a circular stream channel. Two PIT tag loop detectors, placed on a narrow part of the channel, automatically recorded identity and swimming direction of tagged fish. We demonstrate some of the applications in behavioral research, such as individual, general, and diel locomotor activity patterns, rheotactic behavior, and sociograms showing activity relationships among individuals within a group.
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