In: Revised Analyses of Time-Series
Studies of Air Pollution and Health (Lament J, ed).
In the context of GAMs for time-series
data, Dominici et al.
Associations between daily values of pollution and mortality have been extensively examined using time-series
Deterministic chaos may account for the difficulty in time-series
studies of identifying a threshold for the association between fluctuant levels of PM and mortality (1,30,31).
Built with autonomic time-series
performance baselining, behavioral-based problem detection and alerting, real-time, cross-tier root cause analytics and agentless data acquisition, the solution instruments network, server, application, and session and transaction layers in 360 degrees.
IPDRA uses DataMontage to present timelines and time-series
graphs that show many clinical variables at once to help clinicians see significant patterns and trends.
With Crucible, Prediction Dynamics provides a revolutionary new approach to financial time-series
modeling, enabling users to build models that consistently generate stable and accurate predictive signals, even during periods of market stress.
With Crucible, Prediction Dynamics is pioneering a revolutionary new approach to financial time-series
modeling that has the potential to transform the world of quantitative finance," said Dr John Carney, Chief Technology Officer at Prediction Dynamics.
a leading provider of time-series
based decision-support solutions to the world's financial and energy markets, announced two senior management promotions to recognize its North American sales and consulting team sales growth in 2000.
2000's(TM) exceptional technology for handling time-series
data, our clients get the benefit of high performance solutions.
FAME's 18 years' experience in time-series
database management will facilitate the Bank in their migration from the current data management system comprised of relational database and spreadsheet software.
Two famous econometricians formulated the strategy of forecasting a times series called the Box-Jenkins method named after the statisticians George Box and Gwilym Jenkins,  this method applies autoregressive moving average (ARMA) or autoregressive integrated moving average (ARIMA) models to find the best fit of a time-series
model to past values of a time series.