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EDITORS SUMMARY
EDITORS SUMMARY

This PDF is a selection from a published volume from... Bureau of Economic Research Volume Title: Measuring Economic Sustainability and Progress
This PDF is a selection from a published volume from... Bureau of Economic Research Volume Title: Measuring Economic Sustainability and Progress

... data collections that would fill gaps in coverage and develop new methods for better measurement of risk and sustainability in financial markets. If such collections by financial regulators and central banks are designed so as to provide data that meets both the microdata needs of regulators and the ...
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... sample is held out one-by-one and the model is fit with the remaining data. This requires fitting the model n times, once for every point in the data (i.e., n-fold cross validation). We can use cross-validation to set parameter values for a model. For example, we can select a set of possible values ...
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... • Paradigms for distributed computing (MPI and Hadoop) • Nodes work in parallel and combine their results • Allows us to divide and conquer the problem ...
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... • Several more improvements have been made to handle numeric attributes (via univariate splits), missing values and noisy data (via pruning) ...
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... – Expensive (about 2-10 more expensive than Affymetrix) ...
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Introduction to Probability Theory in Machine Learning: A Bird View

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... economic variables in the recent past. A more detailed description of the model and its statistical properties will be provided in the full version of the paper. The objective function penalizes deviations of objective variables from their desired ("ideal") values. Exogenous variables of the model ...
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... • BADC to propose a standard Excel spreadsheet-type template for amateur observers to use. – This would greatly simplify the transmission and storage of amateur observations to BADC. – A mandatory metadata section should be required, perhaps including site plan/s and photographs from cardinal points ...
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... are assigned empirically; find the expected value. For example, find a current data distribution on the number of TV sets per household in the United States, and calculate the expected number of sets per household. How many TV sets would you expect to find in 100 randomly selected households?* Use p ...
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< 1 ... 151 152 153 154 155 156 157 158 159 ... 178 >

Data assimilation

Data assimilation is the process by which observations are incorporated into a computer model of a real system. Applications of data assimilation arise in many fields of geosciences, perhaps most importantly in weather forecasting and hydrology. The most commonly used form of data assimilation proceeds by analysis cycles. In each analysis cycle, observations of the current (and possibly past) state of a system are combined with the results from a numerical model (the forecast) to produce an analysis, which is considered as 'the best' estimate of the current state of the system. This is called the analysis step. Essentially, the analysis step tries to balance the uncertainty in the data and in the forecast. The result may be the best estimate of the physical system, but it may not the best estimate of the model's incomplete representation of that system, so some filtering may be required. The model is then advanced in time and its result becomes the forecast in the next analysis cycle. As an alternative to analysis cycles, data assimilation can proceed by some sort of nudging process, where the model equations themselves are modified to add terms that continuously push the model towards observations.
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