Estimation Theory in Financial Accounting as It Applies to Valuing Intellectual Property Assets

The abandonment option under various capital budgeting models are discussed in this study to illustrate the notion that present value of cash flows is often improperly estimated in financial models utilizing decision analytics in estimation theory as it applies in financial accounting. In this study, intellectual property rights and other intangible assets which are often not considered in the accounting estimation processes utilized in financial accounting. An investor/analyst often misestimates cash flow resulting in less-than-optimum capital budgeting decisions. This is especially a problem when actions to abandon for salvage and other similar decisions improve when the present value of intangibles and property rights are included in the decision process. This last statement is the goal of this study as well as to present well-founded processes to improve abandonment and similar decisions in capital budgeting decisions. The estimation problem in financial accounting is included in the analysis to accomplish this goal.

A study on the construction and application of the evaluation index system for the water conservancy photography creation base

In order to improve the evaluation system for the water conservancy photography creation base, evaluation indicators regarding the aspects of photographic resources, photographic elements, and water resources were selected to construct an evaluation index system, and the evaluation criteria for each index were provided. The optimal comprehensive weight for each evaluation index was determined following the moment estimation theory. The quantitative evaluation of the water conservancy photography creation base was carried out combined with the scoring standards for each index. The evaluation index system constructed here was then discussed in the application. This indicated that the evaluation index system is suitable in determining the construction status of the evaluated cases, thus, verifying its rationality. The comprehensive weighting of the indicators based on the moment estimation theory made the evaluation method more scientific and the corresponding results more reliable. This enabled the entire evaluation system and method to provide the theoretical support for the scientific evaluation of the water conservancy photography creation base.

Robust and Nonrobust Linking of Two Groups for the Rasch Model with Balanced and Unbalanced Random DIF: A Comparative Simulation Study and the Simultaneous Assessment of Standard Errors and Linking Errors with Resampling Techniques

In this article, the Rasch model is used for assessing a mean difference between two groups for a test of dichotomous items. It is assumed that random differential item functioning (DIF) exists that has the potential to bias group differences. The case of balanced DIF is distinguished from the case of unbalanced DIF. In balanced DIF, DIF effects cancel out on average. In contrast, in unbalanced DIF, the expected value of DIF effects can differ from zero and favors a particular group on average. Robust linking methods (e.g., invariance alignment) aim at determining group mean differences that are robust to the presence of DIF. In contrast, group differences obtained from nonrobust linking methods (e.g., Haebara linking) can be affected by the presence of a few DIF effects. Alternative robust and nonrobust linking methods are compared in a simulation study under various simulation conditions. It turned out that robust linking methods are preferred over nonrobust alternatives in the case of unbalanced DIF effects. Moreover, M-estimation theory is used for studying the asymptotic behavior of linking estimators if the number of items tends to infinity. These results give insights into asymptotic bias and the estimation of linking errors that represent the variability in estimates due to selecting items in a test. Moreover, M-estimation theory is also used in an analytical treatment to assess standard errors and linking errors simultaneously. Finally, double jackknife and double half sampling methods are introduced and evaluated in a simulation study to assess standard errors and linking errors simultaneously. Half sampling outperformed jackknife estimators for the assessment of variability of estimates from robust linking methods.