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We investigate the impact of the mixed attribute GAAP measurement model on accrual quality inferences. GAAP rules vary from an income statement "matching" focus to a balance sheet "fair-value" focus. Accrual properties are also affected by the business activity being measured and the activity's recurrence. Furthermore, accrual measurement is affected by managerial estimation error/manipulation. As a consequence, accruals are heterogeneous with predictably different statistical properties. We construct a dataset of more than 100,000 accrual items that Compustat aggregates into data item FOPO. We classify these accruals into 32 types over a 21-year span. We show that variation in persistence for the 32 accrual types is consistent with our predictions concerning GAAP rules. We provide a model of accruals and show that it is implausible for estimation error of reasonable magnitudes to explain this variation. Finally, we develop a measure of reporting consistency and show its impact on accrual quality inferences. [ABSTRACT FROM AUTHOR]

For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang-bang evasive maneuver with a random switching time. Combined Fast multiple model adaptive estimation (Fast MMAE) algorithm, the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration. Introduced the detection error model related to the line-of-sight (LOS) separation angle of two interceptors, an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance. Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion, Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately. The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation. [ABSTRACT FROM AUTHOR]