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I realized that I deal with statistics every day. We covered issues that pertain to real life and I now feel I have knowledge about important issues I was previously unaware about. Overall, the instructor and the assistant instructors were responsive and helpful. The homework grading was done in a timely way and the model answers were helpful.

All in all, I learned a lot and am eager to practically apply these strategies. This was a real eye-opener to me. In short, a real joy to follow this course and be part of this learning process. It also helped me to see links I didn't see before where I could use different methods to improve upon organizations. This course will help me evaluate and code speech recognition tools and develop information extraction models.

It will guide me toward what to consider and keep me from falling into some traps. I fully enjoyed the challenge of working through the assignments and reading Dr. I gained some new insights into regression analysis.

In other words, my horizons were expanded and I learned a great deal. This is the best course so far at statistics. Although this is not a Tableau course, Catherine (and evidently Galit) really did a good job of keeping things direct and simple in regards to step by step instructions for getting from point A to B in the Tableau software so the student could follow easily and therefore complete the assignments with confidence.

Your faculty are an incredible asset, making these classes the best learning experience I've had online. As always it was a pleasure taking a course from Professor Indurkhya. This course was a model of what Statistics. The professor and assistant instructor were incredibly responsive and helpful. This was my second Statistics. It makes the discussion much more organic, relevant, useful, and enjoyable.If you do not have an app for your site yet, consider building one to take advantage of the benefits App Indexing brings, in particular, its deep links.

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It capped a miserable run of form for the Baggies that has seen them claim just two wins in their last 21 league matches. Axing Pulis represents a huge gamble With just two matches remaining in the UEFA Champions League group stages, a lot of the positions are already wrapped up and berths for the knockout spots secured.

But Matchday 5 also sees plenty still in the balance in regards to qualification and subsequently, there are some enormous matches to World Cup qualifying has now ended and we know which 32 teams will battle it out for glory in Russia next summer.

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The teams are neck-and-neck in La Liga with 23 points apiece, which leaves them eight points behind runaway leaders Barcelona. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

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Axing Pulis represents a huge gamble Read new 20 November Champions League Matchday 5: Preview and Tips With just two matches remaining in the UEFA Champions League group stages, a lot of the positions are already wrapped up and berths for the knockout spots secured. But Matchday 5 also sees plenty still in the balance in regards to qualification and subsequently, there are some enormous matches to Read new 17 November Early World Cup 2018 Betting Preview World Cup qualifying has now ended and we know which 32 teams will battle it out for glory in Russia next summer.

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Eliteserien 19:00 Viking - Sogndal 07 July Ireland First Division 21:45 Athlon - Shelbourne 06 July UEFA Europa League 21:30 Jagiellonia - Dinamo Batumi 2. Allsvenskan 20:00 Djurgardens - Kalmar 1. We obtain predictive densities from stochastic volatility (SV) and GARCH models, which we then tilt using the second moment of the risk-neutral distribution implied by options prices while imposing a non-negativity constraint on the equity premium.

By combining the backward-looking information contained in the GARCH and SV models with the forward-looking information from options prices, our procedure improves the performance of predictive densities.

Keywords: entropic tilting, density forecasts, variance risk premium, equity premium, options Suggested Citation: Suggested Citation Waltham, MA 02454-9110United States781. To decline or learn more, visit our Cookies page. This page was processed by apollo4 in 0.

Metaxoglou, Konstantinos and Pettenuzzo, Davide and Smith, Aaron, Option-Implied Equity Premium Predictions via Entropic Tilting (September 9, 2017). To be ranked, a paper must be a publicly available scholarly full-text paper on SSRN. Privately available papers are not considered in these rankings. Eastern, Monday - Friday. Submit a Paper Section 508 Text Only Pages Quick Links Research Paper Series Conference Papers Partners in Publishing Organization Homepages Newsletter Sign Up Rankings Top Papers Top Authors Top Organizations About SSRN Objectives Network Directors Presidential Letter Announcements Contact us FAQs Copyright Terms and Conditions Privacy Policy Cookies are used by this site.

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Benfica - Basel 2-1 Over 2. Manchester United - CSKA Moskva 2-0 1 3. Olympiakos Piraeus - Juventus 0-1 2 5. Liverpool - Spartak Moskva 3-1 1 2.Everything was well organized and complete. We particularly liked having a cell phone for emergencies etc. We loved that the route and accommodations were arranged for us. This took a lot of stress out of the trip. We loved Iceland and will consider returning as well as using Nordic visitor for future travel to other destinations.

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The company did not say how much customers had wagered on Trump-related bets. The marketing for the Paddy Power brand includes a tongue-in-cheek blog, irreverent television advertisements and a variety of stunts. For example, the company sent a hearse to the stadium used by the British soccer team Leicester City after the team fired its manager, Claudio Ranieri, last month, less than a year after winning the English Premier League.

We sent a hearse to Leicester this evening to signal the death of football following the sacking of Claudio Ranieri. The club had a 5000-to-1 chance of winning the league entering the 2015-16 season. Tell us what you think. You must select a newsletter to subscribe to.

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With no seed, the cluster locations can vary from run to run. With a seed, the clusters are deterministic. All the information that you need to recreate or use the cluster on your own. It includes: clusters: a list of centroids with a cluster object for each centroid. It also contains the distance distribution of the entire dataset to that center.

This will be 201 upon successful creation of the cluster and 200 afterwards. Make sure that you check the code that comes with the status attribute to make sure that the cluster creation has been completed without errors. This is the date and time in which the cluster was created with microsecond precision.

In a future version, you will be able to share clusters with other co-workers or, if desired, make them publicly available. This is the date and time in which the cluster was updated with microsecond precision.

A dictionary that gives a numeric summary capturing the distribution of distances from the cluster's center to each of the points that fall into its neighborhood.

A status code that reflects the status of the cluster creation. Example: "My Seed" category optional The category that best describes the anomaly detector. Example: 1 constraints optional An experimental option which adds more predicates to each node in the tree. These predicates help capture expectations about the data, making the tree more sensitive to anomalies.

This option tends to inflate the anomaly scores and requires more CPU time to build and evaluate. However, it also seems to make the trees more effective at flagging anomalous data that was not in the training set. It also seems to improve the forests effectiveness on categorical data.

Specifies the fields that won't be included in the anomaly detector. Example: "MySample" tags optional A list of strings that help classify and index your anomaly detector. Example: 256 With no seed, the anomaly detector locations can vary from run to run.

With a seed, the anomaly detectors are deterministic. This will be 201 upon successful creation of the anomaly detector and 200 afterwards. Make sure that you check the code that comes with the status attribute to make sure that the anomaly detector creation has been completed without errors. This is the date and time in which the anomaly detector was created with microsecond precision. The list of fields's ids that were excluded to build the anomaly detector.

All the information that you need to recreate or use the anomaly detector on your own. It includes the field's dictionary describing the fields and their summaries, the tree structures that makes the model up, and the top anomalies found in the dataset. See the Model Object definition below. Controls whether the frequency of repeated (or very similar) data points lower the anomaly score of the repeats.

In a future version, you will be able to share anomaly detectors with other co-workers or, if desired, make them publicly available. This is the date and time in which the anomaly detector was updated with microsecond precision. A list of top anomalies objects.