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There are numerous examples in which space time structure of variability provides valuable information in understanding and interpreting data and predicting the trend.
A second-order polynomial model was applied for fitting experimental data and predicting the response, and this mathematical model produced a satisfactory fit (R2 = 0.993, p ˂ 0.01).
We investigated if multivariate MPS can be used for the processing of proximal soil sensor data, i.e. interpolating the sensor data and predicting the target variable.
A former baseball statistician, Silver has made his name by aggregating state level polling data, and predicting the likelihood of victory by adjusting for different factors that have historically influenced electoral performance.
Failure to account for cohort effects has implications for interpreting seroprevalence data and predicting the impact of vaccination programmes with dynamic models.
These factors may impact on the existing processes to change mortality over time (as illustrated in Table 2) and make the interpretation of the data and predicting the impact of the new interventions more difficult.
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CLIMATE DYNAMICS AT RAL: www.climate-dynamics.rl.ac.uk Based in England, the Casino-21 project hopes to use a SETI@Home-style screen saver to analyze data and predict the climate of the 21st century.
In all of the cases, the model fitted filter paper hydrolysis data and predicted the sugar profiles and hydrolysis rates.
ELM model can be established by using example data and predict the curve of power in short-term.
Wei et al. (2013) interpolated sparsely distributed magnetometer data and predicted the surface electric field across North America at the geomagnetic storms in 1989 and 2003.
The statistical approaches have been used widely to fit the data and predict the values for return period by many authors.
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