Suchergebnisse

In general, procedures for the analysis of interrupted time series are quite sophisticated and powerful. However, procedures for identifying the intervention component of inter rupted time-series models remain relatively primitive. In this article we demonstrate how exponential smoothing can play a function in the identification of the intervention component of an interrupted time-series model that is analogous to the function that the sample autocorrelation and partial autocorrelation functions serve in the identification of the noise portion of such a model.

ABSTRACTDecision support for managers and policy makers, such as required in planning and evaluation efforts, often requires ad hoc behavioral modeling to account for context‐specific phenomena and to handle data limitations. This paper introduces a systematic approach useful for meeting these requirements in which time‐varying parameter estimation plays an important role. A case study evaluating the impacts of public policy actions on residential natural gas conservation illustrates the approach.

AbstractThere is an ongoing debate on the role of socialization in the development of infants' helping. Although opportunities for the socialization of early helping are rare in problem solving (bystander intervention), there are many opportunities for socialization in participation (working alongside others), and infants' experiences of participation could socialize problem solving indirectly. The present study links participation and problem solving conceptually by drawing on a Hebbian concept of indirect learning and through a study examining mothers' communicative cues in both forms of helping. Forty mother‐infant dyads engaged in two semi‐structured helping tasks, a participation task and a problem‐solving task at five, eight, and ten months of age. Mothers' communicative cues and infants' return of the object were examined using coding schemes adapted from prior research. Mothers used similar communicative cues (reaches, give‐me gestures, and verbal requests) in both tasks, and more maternal scaffolding contributed to greater object handover. Infants showed higher object handover in participation tasks. The findings, framed in Tomasello's neo‐Vygotskian account of prosocial development, offer a synthesis of the debate on the role of socialization where prosocial behavior emerges first between people, and then becomes individualized.

AbstractTheory and empirical research suggest that parental scaffolding of children's participation in chores may contribute to the development of early helping. Sixty mother–child dyads with toddlers between 18 and 24 months of age were assessed on two measures of scaffolding (during a cleanup chore; reading an emotionally laden book together). Children's helping was assessed in five tasks with an experimenter, and children were also assessed for social approach to an unfamiliar adult as a measure of sociability, and for internal state language as a measure of social understanding. Both mothers' scaffolding of everyday helping and children's sociability uniquely predicted individual differences in children's helping. Thus, individual differences in children's helping appear early, and are associated with both temperament and with parents' efforts to support and encourage young children's helpfulness.

ABSTRACTIn recent years, time series analysts have shifted their interest from univariate to multivariate forecasting approaches. Among them, the Box‐Jenkins transfer function process and the state space method have received the most attention. This paper presents a simplified approach that embodies some desirable features of existing methods. It stresses empirical analysis, has a unified modeling structure, is easily applicable, and is adaptive to changes without necessitating prior information on the evolution of a system under study. The core of the method relies on the Carbone‐Longini adaptive estimation procedure (AEP). Results of a comparative study based on the well‐known Lydia E. Pinkham data and the Box‐Jenkins sales/leading indicator data illustrate the merits of multivariate AEP in improving forecasting accuracy while simplifying the analysis process.Subject Area: Forecasting.