Sentences with phrase «best prediction method»

However, what if the answer to «what is the best prediction method» lies in asking people not only who they will vote for, but also who they think will win (as «citizen forecasters» [1]-RRB-, and more importantly, how they feel about who other people think will win?

Not exact matches

While the article wove together a few strands from the common law, it largely built its case for such a right on «recent inventions and business methods» such as «instantaneous photographs and... numerous mechanical devices [that] threaten to make good the prediction that «what is whispered in the closet shall be proclaimed from the house - tops.

Asserting that we do not yet have either the facts or the methods to make forecasting a precise art, Michael argues that there are three basic reasons for continuing to make or act upon them: (1) some forecasts are likely to be close to the mark, (2) poor forecasts provide a better basis for planning than no prediction at all, and (3) well - done forecasts help to illuminate the many factors that interact to produce the future.

I want to use a method, that can be refined, which uses a set of well defined criteria and gives me a fairly reasonable prediction...

These height prediction methods can give you a pretty good idea of what your child's future height will be:

With the failure of traditional forecasting methods to accurately predict the outcomes of the UK General Election of May 2015, can social media based predictions do any better?

Taking into account the well - known pro-Labour bias in the electoral system as well as prediction uncertainty, the method suggested then that the Tories would have a 64 % chance of being the largest party in parliament.

University of Utah chemists Matt Sigman and Anat Milo conducted a study in the journal Nature showing how vibrations in chemical bonds can be used to improve predictions of how chemicals will react — a method that can be used to design better catalysts used to hasten reactions used to make new materials, medicines and industrial products.

Professor Wardlaw, at the University of Edinburgh, said: «We found that putting all visible factors on the scan together gave better prediction, yet most current computer methods do not consider all factors available on the scan and may not be suitable for older patients.

If the successful predictions are confirmed in the mouse model, this strategy may have potential for developing new methods for diagnosis, as well as treatment, of patients with bipolar disorder,» Miyakawa says.

A good example is if you try and fit a normal distribution to 10 data values using a flat prior for the variance... the final variance estimate you get is higher than anything that any of the standard methods will give you, and is really just nonsense: it's extremely biased, and the resulting predictions of the normal are much too wide.

The occasion of the conference provides an opportunity to place sustainable land management (SLM), land tenure, LDN, and the Sustainable Development Goals (SDGs) in a regional and global context, providing the means to enhance or adapted underlying theoretical paradigms, encourage the radical renewal of research methods and the validity of environmental change predictions, as well as to strengthen the integration between social and environmental branches of geography.

In contrast, the OvaCue technology provides a reliable ovulation prediction method for trying - to - conceive women with irregular cycles (as well as women with regular cycles, of course).

Started investigating the theory behind statistical prediction rules and saw that it was a better method for me.

It creates the connections who are very much alike to human «s neurons and unlike the ordinary methods of learning about Forex market it researches the data and its own predictions to multiply the results in a better and more realistic way.

Canadian Ice Service, 4.7, Multiple Methods As with CIS contributions in June 2009, 2010, and 2011, the 2012 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predMethods As with CIS contributions in June 2009, 2010, and 2011, the 2012 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predmethods: 1) a qualitative heuristic method based on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

Canadian Ice Service, 4.7 (+ / - 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

Apply the best validated methods we know for prediction and correction.

It has been shown that precursor methods show better performance compared with other prediction methods (Li et al. 2001; Brajsa et al. 2009).

Totalitarian propaganda raised ideological scientificality and its technique of making statements in the form of predictions to a height of efficiency of method and absurdity of content because, demagogically speaking, there is hardly a better way to avoid disussion than by releasing an argument from the control of the present and by saying that only the future can reveal its merits.

Canadian Ice Service; 5.0; Statistical As with Canadian Ice Service (CIS) contributions in June 2009 and June 2010, the 2011 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic Multi-Year Ice (MYI) extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictors.

Canadian Ice Service, 4.7 (± 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

If you want to do a serious job of using linear methods to predict next years temperature use best linear unbiased prediction.

To remove bias in GIA models, our best method requires comparing Global Positioning System data (GPS) that measures the current bedrock uplift with GIA modeled predictions.

Commercially available 2D and 3D heat transfer models provided good predictions of the thermal bridging in the test walls, as did the parallel path method described in the ASHRAE Handbook of Fundamentals and other texts.

As with previous CIS contributions, the 2016 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness / extent, as well as winter surface air temperature, spring ice conditions and the summer temperature forecast; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent time - series into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

So while it's right to disparage the tomfoolery, it's an abuse of perfectly good statistical tools and analyses to apply them to this prediction; it's a ridiculous prediction from the outset, why smear good statistical methods with the bad premise that they apply here?

His current research includes global ocean modeling and data assimilation efforts as part of Estimating the Circulation & Climate of the Ocean (ECCO) consortium, as well as using ensemble methods for regional ocean analysis and prediction.

A good example is if you try and fit a normal distribution to 10 data values using a flat prior for the variance... the final variance estimate you get is higher than anything that any of the standard methods will give you, and is really just nonsense: it's extremely biased, and the resulting predictions of the normal are much too wide.

Quite egalitarian, so in fact contrarians, scientists who hold ideas outside of the mainstream can prosper provided their ideas have some factual basis and use the scientific method (Scientific method: based on existing obervations pose an hypothesis; using new observations or experiments, test the predictions of that hypothesis; on the basis of the new data either reject the hypothesis or modify it to fit the better understanding, or accept that the initial hypothesis was right at which point it becomes a «theory» or explanatory model).

For decadal scale variations a 60 year cycle, which seems to correlate temperatures and the PDO, is well established see the post» Global Cooling - Methods and Testable Decadal Predictions» at http://climatesense-norpag.blogspot.com.