The current paper reports analyses of the structure of variability in a time-estimation task. Children between 5 and 11 years pressed a button each time they judged that a brief time interval had passed. In two conditions, children either picked their own time interval, their preferred pace, or they were given an imposed pace of 400 ms (2.5 Hz). The resulting trial series were subjected to detr...

One of the most important and valuable goal of software development life cycle is software cost estimation or SCE. During the recent years, SCE has attracted the attention of researchers due to huge amount of software project requests. There have been proposed so many models using heuristic and meta-heuristic algorithms to do machine learning process for SCE. COCOMO81 is one of the most popular...

A survey on opium use was earned out in Tinsukia district of upper Assam to assess the present prevalence and pattern of opium abuse and compared with earlier findings of the year 1981 (Baruah et al., 1995). A total of 75 addicts could be detected during the survey and 61 were interviewed using structured questionnaire. The results indicate significant decline in prevalence in opium use over th...

Learning accurate probabilistic models from data is crucial in many practical tasks in data mining. In this paper we present a new non-parametric calibration method called ensemble of linear trend estimation (ELiTE). ELiTE utilizes the recently proposed ℓ1 trend ltering signal approximation method [22] to find the mapping from uncalibrated classification scores to the calibrated probability est...

The location of spatial sampling points so as to minimize a mean squared error criterion is a common concern in the design of monitoring networks. When the objective is temporal trend estimation, one could seek to minimize the variance of the generalized least-squares estimate of trend. This paper describes a general class of spatio-temporal models possessing separable mean and covari-ance and ...

This paper studies the error in forecasting an autoregressive process with a deterministic component. We show that when the data are strongly serially correlated, forecasts based on a model that detrends the data using OLS before estimating the autoregressive parameters are much less precise than those based on an autoregression that includes the deterministic components, and the asymptotic dis...

The standard approach to time series analysis is to decompose the series into three components, the trend, the seasonal component and the irregular noise. In this paper we are concerned with estimating the trend and so we will assume that all series have been seasonally adjusted. The structural form of the trend is often decided by physical considerations or by inspection of global time series ...

Terrestrial water storage (TWS) estimates retrievals from the Gravity Recovery and Climate Experiment (GRACE) satellite mission were compared to TWS modeled by the Australian Water Resources Assessment (AWRA) system. The aim was to test whether differences could be attributed and used to identify model deficiencies. Data for 2003–2010 were decomposed into the seasonal cycle, linear trends and t...