«Given the size and scope of the IoT and 5G opportunities, we see IDCC's IoT goal as conservative as the company
likely accounts for the uncertainty around monetization strategies and the timing / rate of incremental demand for its IoT related services and products,» analyst Darrin Peller wrote in a note.
Not exact matches
Not only is its central estimate relatively distant from (warmer than) the prior record, but even
accounting for known
uncertainties, and their known shapes, it still emerges as easily the most
likely warmest year on record.
Taking into
account these substantial
uncertainties, Mann et al. (1999) concluded that the 1990s were
likely to have been the warmest decade, and 1998 the warmest year, of the past millennium
for at least the Northern Hemisphere.
It seems
likely to be a combination of factors / definitional differences — as Dr Rogelj says —
account for the difference between the IAM and non-IAM budgets, as both physical climate
uncertainties and technical / societal
uncertainties regarding how much we are able to reduce contributions to warming from non-CO2 matter to estimates of remaining budgets.»
Many physical modelers, and especially climate modelers, seems to think that as long as their models are «science - based» then there is no need to
account for uncertainty in their outputs, notwithstanding that the model parameters are tuned with data, and that aspects of these models are
likely to be ill posed (highly sensitive to small perturbations in the values assigned to parameters).
The fact that we have two opposite conclusions, both with «very
likely» confidence levels, is a classic situation of competing
uncertainties, with the likelihood that both groups are not sufficiently
accounting for the
uncertainties.
While a Trump administration will focus on implementing its own ambitious energy policies, while
likely diminishing President Obama's energy and climate agenda, the realities of political and global ideologies and the inevitability of political transitions should be
accounted for in order to avoid an unsustainable shift in energy policy that is short - lived and introduces more
uncertainty for the U.S. power sector.
Assuming a CR - cloud connection exists, there are various factors which could potentially
account for a lack of detection of this relationship over both long and short timescales studies, including:
uncertainties, artefacts and measurement limitations of the datasets; high noise levels in the data relative to the (
likely low) amplitude of any solar - induced changes; the inability of studies to effectively isolate solar parameters; or the inability to isolate solar - induced changes from natural climate oscillations and periodicities.
This approach allows
for the most
likely class membership to be obtained from the posterior probabilities along with classification
uncertainty; the most
likely class membership variables can then be analyzed to include covariates while
accounting for the measurement error in classification [45].