But it's also interesting
as validation of a model that's becoming increasingly popular: Companies that are private only in name.
They found that genes activated in the mouse model closely mirrored genes known to be activated in infected humans, providing a level
of validation of the model.
The models are not tuned to these events (most «tweaking» is done to match the climatologies, seasonal cycles and diurnal cycles instead) and so they provide a
good validation of the models.
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.
We carried out
validation of the model using a variogram - based procedure, which tested the compatibility of the adopted spatial structure with the data.
The models are not tuned to these events (most «tweaking» is done to match the climatologies, seasonal cycles and diurnal cycles instead) and so they provide a
good validation of the models.
Since the data are historical, the analysis here is essentially that of a hindcast, and since some of these data may have been used during model construction and tuning, it is debatable to what extent they can be considered to
provide validation of the models.
Therefore, transcriptomics, metabolomics, proteomics and high - throughput techniques are used to collect quantitative data for the construction and
validation of models.
«It's sort of
a validation of the model we chose, which was to do something outside of the publisher model, taking all the risk ourselves, putting our own money into it.
I understand the argument that past projections are based on estimated future forcings which can change, but this amounts to the same things as tuning hindcasts and declaring matching a hindcast to observations as
a validation of your model.
How much work is done on
the validation of the models?
Enhance existing efforts to create a comprehensive observing system to document changes in these critical indicators and to provide data for calibration and
validation of models.
Before advocating the expenditures of trillions of dollars for policy measures now the climate modelers should at least demonstrate
this validation of their models.
The ability to duplicate current climate data is an essential step in
the validation of these models and establishing their creditability for projection.
Principles of forecasting require the verification and
validation of models.