Sentences with phrase «analysis models since»

Not exact matches

In case one wishes to discard the record before 1980 from the analysis, it's worth noting that since 1980, the correlation of the FedModel with subsequent S&P 500 total returns has been just 27 %, compared with an average correlation of 90 % for the other models since 1980.

But his key analytical model here, presented as a novel insight» that Progressivism was a movement of the middle class caught between perceived threats from the upper class above and the laboring and farming classes below» has been a commonplace of historiographical analysis since the 1950s.

The paper is a technical analysis of the uncertainties involved in computer modeling studies that use the amount of phosphorus entering Lake Erie in the spring to predict the size of late - summer cyanobacteria blooms, which have grown larger since the mid-1990s.

First - of - its - kind analysis of hundreds of food web models shows that the decrease has mostly taken place since the 1970s

Since joining McLean in 2011, Dr. Mintzopoulos has been developing and implementing MRS and MRI protocols for in vivo studies relevant to models of psychiatric / addiction and neurological conditions, as well as data processing and analysis methods.

Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.

Since the initial star images observed in the near - infrared (IR) bands were significantly blurred, we twice moved the secondary mirror for the focal adjustment based on the results of model analyses as well as data analyses of the near - IR images.

Prospective analyses regarding incident CMD were stratified by sex, since interactions with sex were observed in the 5 years later model (LR test for sex interaction: GHQ 2 years later, P = 0.26: GHQ 5 years later, P = 0.05).

«It's the first Ridgeline that Honda's released since the 2014 model, and our analysis of professional reviews and data shows that versatility is the name of the Ridgeline's game,» say US News.

«It's the first Ridgeline that Honda's released since the 2014 model, and our analysis of professional reviews and data shows that versatility is the -LSB-...]

This success was facilitated by Amazon's careful analysis of previous failed attempts to commercialize ebooks since the early 1990s, and earlier theoretical models developed since the 1930s.

In that sense all analysis of stock market based on historical metrics do nt make much sense since composition of stocks is entirely different in different era and as more capital efficient business model evolve and their time to market cycle shrinks stocks likely to command higher valuations and suddenly lower valuations during short period of time like already happening for many technology companies and as influence of technology on overall cost structure of companies increases (for example: robotics replace many of employees cost etc) valuation matrix of most companies likely to get affected dynamically in short duration of time than in the past.

I am extremely worried about his calcium / phosphorus ratio since the vital essentials is prey model with no guaranteed analysis.

It appears to me that if the HadCRUT3 data since 1980 were modeled with a least - squares analysis, assuming an exponential function, that it would likely model the data better than the green line for the period.

In fact our real argument turned around is that we reject a model amplification of 1.2 and even 1.0 over land since that is inconsistent with the observational analysis of observed ratios of surface and lower troposphere trends.

Typo, first para under reananlyses: «Since weather forecasts (the «analyses») have got much better over the years because computers are faster and models are more skillful.»

Your model must match the data to be credible, while my simple analysis of the Solar effect alone does not need to match the data perfectly, in my paper I say that only approximately 50 % of the warming since 1900 is related to the sun and from 1600 to 1900 the match is quite good, indeed!

We also note that currently all analyses / studies of the models necessarily are in the short term range, making easy to create strawman arguments (eg, since models don't claim to be accurate short - term) especially those arguments that also ignore the law of large numbers.

The animated figure above shows global temperature anomalies for every month since 1880, a result of the Modern - Era Retrospective analysis for Research and Applications, version 2 (MERRA - 2) model run by NASA's Global Modeling and Assimilation Office.

Since the IPCC fourth assessment, several independent analyses of the characteristics of the various models have been published in the scientific literature.

Note that the Kaufmann's paper is very careful in keeping this 60 - year cycle out of consideration by starting the analysis of their forcings in 1950 and running the climate model only since 1999 up to 2008 -LRB-?)

[71] Se the books of Robert Tisdale http://bobtisdale.wordpress.com/ for many analyses of the ocean surface temperatures continuously observed by satellites since 1982 and extensive comparisons of model outputs with observations

for lack of warming since 1998» refers to a model that does address serial correlation (being based on Kaufman, A., H. Kauppi, and J. H. Stock, 2006: «Emissions, concentrations and temperature: a time series analysis.»

«they'd be mixing apples and oranges» — since they were in fact dealing with apples and oranges (analyses from models vs an analysis from observed data) that is surely what they ought to have done!

c) Average sunspot number prediction by a low - frequency modulation model (dotted curve) based on frequency analysis from sunspot and cosmogenic isotope records, compared to the average sunspot number since 1750 (continuous curve).

However, statistical analysis very clearly support the theory, which also imply that the climate sensitivity to CO2 doubling is about 1.5 K. And models made using this hypothesis are able to explain the temperature patterns since 1850 very well, much better than any IPCC CMIP5 models.

We prefer this result since it was based on a comprehensive analysis using extensive proxy data from both land and ocean in combination with an ensemble of climate model simulations, in a paper focused entirely on LGM cooling.

«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).&rModel 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).&rmodel 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).»

Scientific progress since the Third Assessment Report (TAR) is based upon large amounts of new and more comprehensive data, more sophisticated analyses of data, improvements in understanding of processes and their simulation in models and more extensive exploration of uncertainty ranges.

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.

Indeed, the lack of agreement between the model's «hindcast» and actual temperatures since 1995 should remind us again to view this only as a very preliminary analysis with predictive ability that is much more qualitative than quantitative.

Analyses of the CMIP5 models will provide some insight here since the historical simulations have been extended to 2012 (including the last solar minimum), and have updated aerosol emissions.

Although the science of regional climate projections has progressed significantly since last IPCC report, slight displacement in circulation characteristics, systematic errors in energy / moisture transport, coarse representation of ocean currents / processes, crude parameterisation of sub-grid - and land surface processes, and overly simplified topography used in present - day climate models, make accurate and detailed analysis difficult.

Since such analyses require that like is compared with like, rainfall simulations in climate models are often «masked» to match the area covered by available observations.

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 moSince 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 mosince 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.

Note: This analysis has been revised since its original publication based on our latest model of active iPhone handsets in the U.S. for 2016.

Moreover, the subgroups presented in the figures are not similar to the analyses in the statistical models since the statistical analyses of the environmental factors are based on scaled variables.

In addition, since from a practical - clinical perspective effect sizes are the most relevant objective of the analyses, and due to the fact that p - values are strongly dependent on sample size, all effect sizes for the relationships analyzed have been estimated by the confidence interval for the parameters, with the R2 measuring the global predictive capacity of the models (adjusted to the covariates).