The network autocorrelation model has been extensively used by researchers interested modeling social influence effects in social networks. The most common inferential method in the model is classical maximum likelihood estimation. This approach, however, has known problems such as negative bias of the network autocorrelation parameter and poor coverage of confidence intervals. In this paper, w...

Given the recent trend towards validating the neuroimaging statistical methods, we compared the most popular functional magnetic resonance imaging (fMRI) analysis softwares: AFNI, FSL and SPM, with regard to temporal autocorrelation modelling. We used both resting state and task-based fMRI data, altogether 10 datasets containing 780 scans corresponding to different scanning sequences and differ...

Finding a low-interference connected topology is a fundamental problem in wireless sensor networks (WSNs). The problem of reducing interference through adjusting the nodes’ transmission radii in a connected network is one of themost well-known open algorithmic problems in wireless sensor network optimization. In this paper, we study minimization of the average interference and the maximum inter...

1. Individuals can show positive correlations in performance (e.g. growth and reproduction) through time beyond the effects of size or age. This ‘performance autocorrelation’ has been attributed previously to traits that differ among individuals or to extrinsic generators of environmental heterogeneity. 2. A model of mobile consumers on a dynamic resource showed that consumer foraging gave rise...

In functional magnetic resonance imaging statistical analysis there are problems with accounting for temporal autocorrelations when assessing change within voxels. Techniques to date have utilized temporal filtering strategies to either shape these autocorrelations or remove them. Shaping, or "coloring," attempts to negate the effects of not accurately knowing the intrinsic autocorrelations by ...

We have used aperiodically poled lithium niobate waveguides to perform intensity autocorrelation and frequency-resolved optical gating (FROG) measurements for ultraweak femtosecond pulses at 1.5 microm wavelength. The required pulse energies for intensity autocorrelation and FROG are as low as 52 aJ and 124 aJ, respectively. The corresponding sensitivities are 3.2 x 10(-7) mW(2) and 2.7 x 10(-6...

To estimate a time series model for multiple individuals, a multilevel model may be used. In this paper we compare two estimation methods for the autocorrelation in Multilevel AR(1) models, namely Maximum Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo. Furthermore, we examine the difference between modeling fixed and random individual parameters. To this end, we perform a sim...

Virtually all remotely sensed data contain spatial autocorrelation, which impacts upon their statistical features of uncertainty through variance inflation, and the compounding of duplicate information. Estimating the nature and degree of this spatial autocorrelation, which is usually positive and very strong, has been hindered by computational intensity associated with the massive number of pi...

Minimum-maximum effort intervals are applied in the planning of software development projects in order to, among other things, determine the contingency buffer. Several studies suggest that judgment-based minimummaximum intervals are based on a systematic over-confidence in the accuracy of the effort estimates. In this paper, we investigate whether the possession by estimators of information ab...