For 48 brands in diverse industries, vector autoregressive models show that volume metrics explain the most for brand awareness and purchase intent, while bottom-up SETs excel at explaining brand impression, satisfaction and recommendation. Systematic differences yield contingent advice: the most nuanced ...
Thus, we estimate a large non-stationary dynamic factor model using principal components (PC) as suggested by Bai (J Econom 122(1):137鈥 183, 2004), where the estimated common factors are used in a factor-augmented vector autoregressive model to forecast the Global Index of Economic Activity...
aThe simplest form of the spatially lagged weight matrix model is also referred to as the autoregressive model, 空间地滞后的重量矩阵模型的简单形式也指自回归模型, [translate] a欣赏自然风光, Appreciates the natural scenery, [translate] aTOM会讲一点汉语 TOM can speak a Chinese [translate] a5区又...
Gupta, R., M. Jurgilas, A. Kabundi, and S.M. Miller. 2012. Monetary policy and housing sector dynamics in a large-scale bayesian vector autoregressive model.International Journal of Strategic Property Management16 (1): 1–20. Google Scholar Gupta, R., M. Jurgilas, S.M. Miller, and ...
In response to the highly variable cloud loads, Gupta et al. [26] proposed an online adaptive method for predicting cloud resource usage time series. This method converts the batch-processing Autoregressive Integrated Moving Average (ARIMA) model into an online model to handle the streaming nature...
In this paper we establish the asymptotic distribution of the quasi-maximum likelihood (QML) estimator for generalized autoregressive conditional het- eroskedastic (GARCH) processes, when the true parameter may have zero coefficients. This asymptotic distribution is the projection of a normal vector dis...
【报告题目】Model Checking for Functional Linear Models 【报告摘要】 In this paper, we study the goodness-of-fit test for functional linear models and propose a test statistic which is based on a residual marked empirical process. The test can overcome the poor performance problem due to the ...
In response to the highly variable cloud loads, Gupta et al. [26] proposed an online adaptive method for predicting cloud resource usage time series. This method converts the batch-processing Autoregressive Integrated Moving Average (ARIMA) model into an online model to handle the streaming nature...
Determination of the cointegration rank is an important part of analyzing the cointegrated vector autoregressive model in the framework of Johansen (1988, 1991, 1995), Johansen and Juselius (1990), and Juselius (2006). We consider the rank deficient case where the cointegration rank of the data ...
One simple alternative to conventional longitudinal data analysis methods is to calculate the area under the curve (AUC) from repeated measures and then use this new variable in one’s model. The present study assessed the relative efficacy of two AUC measures: the AUC with respect to the ...