Sentences with phrase «parameter estimates from»

The best - fitting estimates of the sibling control and statistical covariate model are based on parameter estimates from model 4.

New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE - 2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as «The Cannon»; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total).

Comparisons with stellar parameter estimates from the literature show good agreement within uncertainties.

But model x and model y are apparently measurements from a «holdout», or «verification» period, using parameters estimated from a distinct calibration period, and hence RE.gt.0 is not mathematically enforced.

All these studies depend on inferring the statistical properties of the time - series from an assumed noise model with parameters estimated from the residuals.

Not exact matches

This means that the degree of consciousness attained by living creatures (from the moment, naturally, when it becomes discernible) may be used as a parameter to estimate the direction and speed of Evolution (that is to say, of the Cosmic Coiling) in terms of absolute values.

We therefore performed each simulation 2,000 times, drawing key parameters at random from triangular distributions covering the range of estimates available in the literature associating breastfeeding with maternal health outcomes, centered on the point estimate provided in the literature and a distribution width of four standard errors.

«New satellite method enables undersea estimates from space: Statistical advance quantifies important ocean parameters in the illuminated ocean.»

Although estimates of this parameter, based on observations, are very uncertain, observers generally quote values in the range from 50 to 90 kilometres per second per megaparsec.

By measuring subtle variations in the cosmic microwave background (CMB), the remnant radiation from the early universe that pervades the sky, WMAP refined the estimated age of the universe (13.7 billion years, give or take), among other key cosmological parameters.

Coalescence - based modeling of demographic parameters estimate that the first domesticated rice population to split off from O. rufipogon was O. sativa ssp.

Where (equilibrium / effective) climate sensitivity (S) is the only parameter being estimated, and the estimation method works directly from the observed variables (e.g., by regression, as in Forster and Gregory, 2006, or mean estimation, as in Gregory et al, 2002) over the instrumental period, then the JP for S will be almost of the form 1 / S ^ 2.

We extracted the parameter estimates for each subject and each condition from the two regions where there were significant group effects at rest, and ran a two - way ANOVA (group × condition) for each model (theta and gamma).

Finnish Meteorological Institute has been doing estimates of two essential sea ice parameters — namely, sea ice concentration (SIC) and sea ice thickness (SIT)-- for the Bohai Sea using a combination of a thermodynamic sea ice model and Earth observation (EO) data from synthetic aperture radar (SAR) and microwave radiometer.

The APOGEE red - clump (APOGEE - RC) catalog contains photometry from 2MASS, reddening estimates, distances, line - of - sight velocities, stellar parameters and elemental abundances determined from the high - resolution APOGEE spectra, and matches to major proper motion catalogs.

Using Mg / Ca paleothermometry from the planktonic foraminifera Globigerinoides ruber from the past 500 k.y. at Ocean Drilling Program (ODP) Site 871 in the western Pacific warm pool, we estimate the tropical Pacific climate sensitivity parameter (λ) to be 0.94 — 1.06 °C (W m − 2) − 1, higher than that predicted by model simulations of the Last Glacial Maximum or by models of doubled greenhouse gas concentration forcing.

Indian scientists made direct contributions — ranging from designing algorithms used to analyse signals registered by detectors to ascertain those from a gravitational wave to working out parameters like estimating energy and power radiated during merger, orbital eccentricity and estimating the mass and spin of the final black hole and so on.

Model 4 shrinks parameter estimates away from extreme values, mitigating the risk of overfitting the data.

Estimates of the parameters were calculated only from the chains that had reached adequate convergence.

This survey should provide an updated list of breeding sites, a good estimate of the size of the population, and data about survival rate of different age classes: together with the high resolution data from our intensive study of Sea Lion Island this new information should provide the parameters needed to determine the current status of the population and forecast its future.

This is visualized in figure 4 where ensemble members from the CCSM4 AR4 runs are fit with S - shaped (Gompertz) functions using the 1979 - 2011 period to estimate the parameters.

Using Mg / Ca paleothermometry from the planktonic foraminifera Globigerinoides ruber from the past 500 k.y. at Ocean Drilling Program (ODP) Site 871 in the western Pacific warm pool, we estimate the tropical Pacific climate sensitivity parameter (λ) to be 0.94 — 1.06 °C (W m − 2) − 1, higher than that predicted by model simulations of the Last Glacial Maximum or by models of doubled greenhouse gas concentration forcing.

If the modeled results from scenario c (with best possible parameter estimates and counterfactual CO2 assumptions) continue for a sufficient time to be closer to actual data than the modeled results from scenarios a and b (with best possible estimates of parameters and accurate CO2 assumptions), then the model that produced the computed results will have been disconfirmed.

If we calibrate a driver / response relationship based on a criterion of some minimal correlation (or probability) from a linear model, but the calibration period from which that derives only actually samples some part of a more complex, non-linear response surface / curve, then the estimates of the parameter of interest in times past could be seriously wrong and / or the certainty in the parameter over-estimated.

This parameter is estimated for both Arctic and Antarctic from the daily brightness temperature maps from SSM / I.

The model estimates all parameters simultaneously, and the structure of the model allows poorly known species to draw strength from the rest of the flora.

Do you have methodological or philosophical objections to estimating parameters from data?

Most fundamentally, the inference revolves around assuming that there exists a linear relationship, and estimating parameters in the linear relationship from climate models.

These estimates of the entropy are shown in Figure 6, and it is clear that the entropy determined from physical parameters such as the F10.7 flux and solar magnetic field shows variations similar to those in the entropy obtained from the sunspot number.

Providing you can sufficiently constrain a more primitive model, i.e. ensure that all its parameters can be determined / estimated from observables, I do not see the problem.

The key parameter, sensitivity, is estimate from several lines of empirical evidence.

For any assumed distribution of parameter values, a method of producing 5 — 95 % uncertainty ranges can be tested by drawing a large number of samples of possible parameter values from that distribution, and for each drawing a measurement at random according to the measurement uncertainty distribution and estimating a range for the parameter.

At a recent debate at Oxford University, organized by the OU Engineering Society, I gave the undergraduates an argument from process engineering (which you will find in outline in my Union College presentation, and in more detail in my Hartford College lecture) to the effect that the closed - loop temperature - feedback gain in the climate system (i.e., the product of the Planck parameter and the net sum of all unamplified feedbacks) can not much exceed 0.1, implying at most 1.3 K of warming per CO2 doubling, compared with the IPCC's central estimate of 3.3 K.

While GEV shape parameter estimates are predominately negative, qualitatively showing weak evidence for the Fréchet form of the GEV distribution, field significant differences from the Gumbel distribution in the region are not found.

A little amusingly, the official 2007 Intergovernmental Panel on Climate Change estimates arose from a survey of contemporary IAMs, which now tend to cite the IPCC's parameters as gospel.

By comparing values of these parameters from the mid-19 century to now, they can estimate how much the earth warmed in association with human greenhouse gas emissions.

Estimates of natural variability from an AOGCM provide a critical input in deriving, by comparing temperature estimates from the simple model with observations, a likelihood function for the parameters jointly at each possible combination of parameter settings (and in one or two cases AOGCMs provide surrogates for some of the observationEstimates of natural variability from an AOGCM provide a critical input in deriving, by comparing temperature estimates from the simple model with observations, a likelihood function for the parameters jointly at each possible combination of parameter settings (and in one or two cases AOGCMs provide surrogates for some of the observationestimates from the simple model with observations, a likelihood function for the parameters jointly at each possible combination of parameter settings (and in one or two cases AOGCMs provide surrogates for some of the observational data).

Values for that parameter are sufficient to estimate the time span for the gas released from a sample, given the length of the sample.

Then estimate underlying parameters from observed growth and other aspects of the state that might be observed.

The role of stochastics is then even more crucial: (a) to infer dynamics (laws) from past data; (b) to formulate the system equations; (c) to estimate the involved parameters; and (d) to test any hypothesis about the dynamics.

I think it is fair to say that a lot of readers agree that you have a model with a high correlation to the data from which the parameters have been estimated.

«The assessment is supported additionally by a complementary analysis in which the parameters of an Earth System Model of Intermediate Complexity (EMIC) were constrained using observations of near - surface temperature and ocean heat content, as well as prior information on the magnitudes of forcings, and which concluded that GHGs have caused 0.6 °C to 1.1 °C (5 to 95 % uncertainty) warming since the mid-20th century (Huber and Knutti, 2011); an analysis by Wigley and Santer (2013), who used an energy balance model and RF and climate sensitivity estimates from AR4, and they concluded that there was about a 93 % chance that GHGs caused a warming greater than observed over the 1950 — 2005 period; and earlier detection and attribution studies assessed in the AR4 (Hegerl et al., 2007b).»

Using feedback parameters from Fig. 8.14, it can be estimated that in the presence of water vapor, lapse rate and surface albedo feedbacks, but in the absence of cloud feedbacks, current GCMs would predict a climate sensitivity (± 1 standard deviation) of roughly 1.9 °C ± 0.15 °C (ignoring spread from radiative forcing differences).

Estimating the Hurst parameter from observed data is very tricky business.

So yes, you don't know the changes in the tails with the same confidence as the middles, and you never will, but you can have some pretty strong and defensible clues based on the totality of the evidence coming from the estimated changes in various parameters of the distribution.

Where (equilibrium / effective) climate sensitivity (S) is the only parameter being estimated, and the estimation method works directly from the observed variables (e.g., by regression, as in Forster and Gregory, 2006, or mean estimation, as in Gregory et al, 2002) over the instrumental period, then the JP for S will be almost of the form 1 / S ^ 2.

«The Planck feedback parameter [equivalent to κ — 1] is negative (an increase in temperature enhances the long - wave emission to space and thus reduces R [the Earth's radiation budget]-RRB-, and its typical value for the earth's atmosphere, estimated from GCM calculations (Colman 2003; Soden and Held 2006), is ~ 3.2 W m2ºK — 1 (a value of ~ 3.8 W m2ºK — 1 is obtained by defining [κ — 1] simply as 4σT3, by equating the global mean outgoing long - wave radiation to σT4 and by assuming an emission temperature of 255 ºK).»

Calibration and tuning of coupled Human — Earth System models, as indicated above, could take advantage of optimal parameter estimation using advanced Data Assimilation, rather than following the more traditional approach of tuning individual parameters or estimating them from available observations.

On the other hand we have the observed data that may be described by a certain process (or perhaps by several different processes), and we can try to estimate from the data the true structure and values for the parameters.

Reviewed and analyzed all parameters of the litigated claim.Compared estimate, expert reports and all data from damaged property and or injury.