EXPLORING MARKET PRICING STRATEGIES VIA DYNAMIC PROGRAMMING

Price determinants as well as strategies can be studies by use of simulation, particularly if cost and price relationships can be related to market activity [1] [9] [11]. But, through the use of dynamic programming, given the market conditions, one can extend the analysis to include an optimal strategy. This paper describes a dynamic programming approach to studying price strategy. A model is developed to show that in a market characterized by cost/volume and price/volume relationships, profitability can be extended beyond that resulting from a dominant market strategy to an optimal maximizing strategy. Extension of the model is suggested for studying (a) sensitivity of a strategy (solution) to price level and cost changes, (b) optimal timing of withdrawal, and (c) present value analysis.     

DECISION RULES IN PRODUCTION PLANNING UNDER CHANGE-CONSTRAINED SALES*

Alternative decision rules for aggregate production scheduling are specified here under chance-constrained sales and compared with the HMMS model. These rules are evaluated for their performance on the basis of simulated data on sales and it is found that the linear decision rules of the HMMS model can be considerably improved.     

EXPERIMENTAL RESULTS OF AN APPROACH FOR EVALUATING MULTIATTRIBUTE ALTERNATIVES

In this paper the results of an extensive simulation study are reported to provide empirical evidence on the Evaluation and Bound approach. Some rules for implementing the procedure interactively on a computer are also examined and compared experimentally. The results suggest that the Evaluation and Bound procedure, in conjunction with an appropriate strategy of implementing it, would reduce considerably the information requirement of the decision maker in the choice of a preferred multiattribute alternative.     

A new approach to statistical efficiency of weighted least squares fitting algorithms for reparameterization of nonlinear regression models

We study nonlinear least-squares problem that can be transformed to linear problem by change of variables. We derive a general formula for the statistically optimal weights and prove that the resulting linear regression gives an optimal estimate (which satisfies an analogue of the Rao-Cramer lower bound) in the limit of small noise.     

Population structure and correlation between auxiliary and target variables may affect precision of estimates in forest inventory

Simulations of forest inventory in several populations compared simple random with “quick probability proportional to size” (QPPS) sampling. The latter may be applied in the absence of a list sampling frame and/or prior measurement of the auxiliary variable. The correlation between the auxiliary and target variables required to render QPPS sampling more efficient than simple random sampling varied over the range 0.3–0.6 and was lower when sampling from populations that were skewed to the right. Two possible analytical estimators of the standard error of the estimate of the mean for QPPS sampling were found to be less reliable than bootstrapping.     

Accounting for Uncertainty in Heteroscedasticity in Nonlinear Regression

Toxicologists and pharmacologists often describe toxicity of a chemical using parameters of a nonlinear regression model. Thus estimation of parameters of a nonlinear regression model is an important problem. The estimates of the parameters and their uncertainty estimates depend upon the underlying error variance structure in the model. Typically, a priori the researcher would not know if the error variances are homoscedastic (i.e., constant across dose) or if they are heteroscedastic (i.e., the variance is a function of dose). Motivated by this concern, in this paper we introduce an estimation procedure based on preliminary test which selects an appropriate estimation procedure accounting for the underlying error variance structure. Since outliers and influential observations are common in toxicological data, the proposed methodology uses M-estimators. The asymptotic properties of the preliminary test estimator are investigated; in particular its asymptotic covariance matrix is derived. The performance of the proposed estimator is compared with several standard estimators using simulation studies. The proposed methodology is also illustrated using a data set obtained from the National Toxicology Program.     

Let Me Go: The Influences of Crawling Experience and Temperament on the Development of Anger Expression

Infants’ emerging ability to move independently by crawling is associated with changes in multiple domains, including an increase in expressions of anger in situations that block infants’ goals, but it is unknown whether increased anger is specifically because of experience with being able to move autonomously or simply related to age. To examine the influence of locomotion on developmental change in anger, infants’ (N = 20) anger expressions during an arm restraint procedure were observed longitudinally at a precrawling baseline assessment and 2 and 6 weeks after the onset of crawling. Infant age at each crawling stage was unrelated to the frequency of anger expressed in response to arm restraint. At 6 weeks postcrawling onset, infants whose mothers rated them as temperamentally higher in distress to limitations, compared with those rated lower, showed a greater increase in the frequency of anger expressed during the arm restraint relative to earlier assessments and took longer to reduce the frequency of anger expressed when no longer restrained. Findings suggest that experience with autonomous crawling has an effect on anger expression, independent of age, and that a temperamental tendency to become distressed by limitations may exacerbate the effect of crawling on anger expression.     

Social Cognitive Factors,Support, and Engagement: Early Adolescents’ Math Interests as Precursors to Choice of Career

The authors examined the central hypothesis that students’ early perceptions of support and sense of engagement in math classes and math activities strongly influence the broadening or narrowing of their math interest. The focus was on the first wave of qualitative data collected from 5th‐, 7th‐, and 9th‐grade students during the 2007–2008 academic year as part of a longitudinal study. Findings indicate the importance of using group work and extrinsic motivation in middle school math classes to broaden interest; peer classroom behavior was often a detractor of math interest.     

Effortful Control Mediates Relations Between Children's Attachment Security and their Regard for Rules of Conduct

Although attachment security has been associated with children's rule‐compatible conduct, the mechanism through which attachment influences early regard for rules is not well established. We hypothesized that effortful control would mediate the link between security and indicators of children's emerging regard for rules (discomfort following rule violations, internalization of parents’ and experimenter's rules, few externalizing behaviors). In a longitudinal study, the Attachment Q‐Set was completed by parents, effortful control was observed, and Regard for Rules was observed and rated by parents. The proposed model fit the data well: Children's security to mothers predicted their effortful control, which in turn had a direct link to a greater Regard for Rules. Children's security with fathers did not predict effortful control. The mother‐child relationship appears particularly important for positive developmental cascades of self‐regulation and socialization.