The structural uncertainty represents the uncertainty inherent in the DNDC model and is set using
independent validation data (directly measured daily methane fluxes on benchmark sites) available at the time of methodology publication.
Not exact matches
Any results that are reported to constitute a blinded,
independent validation of a statistical model (or mathematical classifier or predictor) must be accompanied by a detailed explanation that includes: 1) specification of the exact «locked down» form of the model, including all
data processing steps, algorithm for calculating the model output, and any cutpoints that might be applied to the model output for final classification, 2) date on which the model or predictor was fully locked down in exactly the form described, 3) name of the individual (s) who maintained the blinded
data and oversaw the evaluation (e.g., honest broker), 4) statement of assurance that no modifications, additions, or exclusion were made to the
validation data set from the point at which the model was locked down and that neither the
validation data nor any subset of it had ever been used to assess or refine the model being tested
The team then selected a subset of
data for developing a panel for differentiating between pancreatic cancer and healthy pancreas tissue and thereafter applied this «Pancreatic Cancer Predictor» to the remaining datasets for
independent validation to confirm the accuracy of the markers.
Well, it seems that the ACT report card and the other
data represent a
validation of educator performance
independent of the dreaded and vilified TAKS and STAAR assessments, including the significant disconnect with the graduation statistics.
[Response: The satellite altimeter
data point is shown in our Vermeer & Rahmstorf 2009 paper as an
independent validation point that was not used for calibration, and it fits the relationship perfectly.
Parameters are determined with
data independent from that to be used for the
validation test.
Such reliance is
data intensive and hence
independent validation of terrestrial system models is problematical.
However, when a
validation was performed on a similar analysis for which the regression model was calibrated with a subset of the
data, and the remaining
data were used for
validation, it became apparent that models based on the factors that McKitrick & Michaels used had no skill (i.e. were not able to reproduce the
independent data).
Oreskes (1998) argues for model evaluation (not
validation), whereby model quality can be evaluated on the basis of the underlying scientific principles, quantity and quality of input parameters, the ability of a model to reproduce
independent empirical
data.
Fully
independent reconstructions will allow mutual
validation during their overlapping time intervals and spectral ranges and will help test methods for fusing high - and low - resolution paleoclimate
data.
But if you are concerned about truth, science, reconciliation of
data,
independent validation of results, etc. etc. do it where you can make a difference.
Furthermore, since the
data are historical, the analysis here is essentially that of a hindcast, and it is debatable to what extent the
data can be considered to provide truly
independent validation of the models.
I agree there are other possibilities, but if we believe that adjustments are relatively unimportant (Nick's work seems pretty persuasive here as
independent validation of BESTs work), to me the most plausible candidate is spatial sampling effects (note this is really tempo - spatial, since there could be differences in the amount of annual
data used at the same site between the series).
But according to a so - called «
validation study» conducted by an unbiased
independent researcher, a Dr. Edward Jo from the California State Polytechnic University, the
data reported by the three wearable gadgets in question is not just in average off by 20 beats per minute compared to a separate, much more precise heart rate supervisor, but also «sporadic», «ambiguous», and «all over the place.»