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Tilray dethrones Canopy Growth as the most valuable marijuana stock (TLRY, CGC) | Markets Insider
Tilray dethrones Canopy Growth as the most valuable marijuana stock (TLRY, CGC) September 19, 2018 at 11:12PM https://ift.tt/2QLFcft

Tilray hit a market cap of more than $14 billion on Tuesday, making it worth more than the previous title-holder Canopy Growth. 

Tilray's market cap has exploded by more than 800% since its July IPO.

Follow Tilray's stock price in real-time here. 

Tilray's explosive growth this week, a 29% through Tuesday, has left the Canadian cannabis producer with a larger market cap than Canopy Growth, which has held the title of largest publicly traded marijuana company. 

As of Tuesday's close, Tilray was worth $14.44 in book value, compared to Canopy Growth's $10.91, thanks to its more than 800% gain since its July initial public offering.

On Tuesday, Tilray climbed 29% following the news it had been approved as the first cannabis company to export legal weed into the US for a clinical trial to treat essential tremor, or ET, at the University of California at San Diego.

The stock is up another 40% in pre-market trading Wednesday after CEO Brendan Kennedy appeared on CNBC's "Mad Money" Tuesday evening. He told host told the host Jim Cramer that Canada was just the tip of the iceberg for full legalization when it came to marijuana.

"I think you'll see the third country within 12 months of October, and that's where the real opportunity is," he said. "It's not about Canada — it's about all the countries that follow."

Outside of pharmaceuticals, the cannabis sector's strength has also come from deals with beverage companies like Constellation Brands, the global behemoth behind Corona that owns a 8.5% stake in Canopy Growth.

"It's a great hedge for them," Kennedy told Cramer. "Whether you're an alcohol or an investor in an alcohol company, this is a global opportunity."

Canopy Rivers, the venture capital arm of Canopy Growth which takes minority stakes in smaller, private companies, is set to begin trading on the Toronto Stock Exchange on Thursday.

More Markets Insider cannabis coverage:

Coca-Cola is 'closely watching' the cannabis space — and is reportedly eyeing a deal with one of Canada's biggest producers

The 'world's biggest legal-pot dealer' talks about taking his company public and the future of weed

SEE ALSO: Canadian cannabis producer Tilray is going bananas after its CEO appears on Cramer's "Mad Money"

Join the conversation about this story »

NOW WATCH: One bite from this tick could ruin red meat for the rest of your life

via Chart Of The Day https://ift.tt/2LJTYAn
iftt  All  Feeds  Statistics  EVC 
yesterday by leconeyc
A personal essay on Bayes factors
I would have said nobody blogs like this anymore, and I am very happy to be very wrong.
have_read  model_selection  bayesianism  statistics  psychology  social_science_methodology  via:tslumley 
yesterday by cshalizi
Comprehensive Guide To Massage Envy Sexual Assault Complaints & Lawsuits [Infographic]
Comprehensive Guide To Massage Envy Sexual Assault Complaints & Lawsuits September 19, 2018 at 12:59PM https://ift.tt/2NpxWrp Dozens of women have stepped forward, accusing therapists at Massage Envy locations of committing sexual assault during massage sessions. In civil lawsuits, assault survivors say Massage Envy created a corporate culture in which misconduct was ignored and allowed to continue. Learn more in this infographic from AbuseGuardian.com. via Infographic Journal https://ift.tt/2LtQepB
iftt  All  Feeds  Statistics  EVC 
yesterday by leconeyc
The Ising model
A simple and complete derivation of the classical Ising model.
statistical_physics/thermodynamics  ising  physics  statistics  magnetism  reference 
yesterday by jkglasbrenner
MCMC and the Ising Model | Tanya Schlusser
The Metropolis-Hastings method using both PyMC3 and standard techniques, demonstrated via the Ising model.
statistical_physics/thermodynamics  statistics  tutorial  ising  mcmc  monte_carlo  physics  metropolis  hastings  pymc3  python 
yesterday by jkglasbrenner
The Definitive Guide To Classic Bavarian Costumes [Infographic]
The Definitive Guide To Classic Bavarian Costumes September 19, 2018 at 11:28AM https://ift.tt/2Dd3f44 After some confusion and scandals about certain Oktoberfest costumes, the team at Katoni decided to break down the classic attire into a visual guide. They go through every element of the costume for men and women so you can be confident when going to your local Oktoberfest. via Infographic Journal https://ift.tt/2LtQepB
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yesterday by leconeyc
What Problems Can Billionaires Solve? [Infographic]
What Problems Can Billionaires Solve? September 19, 2018 at 11:28AM https://ift.tt/2NrZsEP People around the planet are facing a myriad of challenges that feel almost impossible to solve. Things like rising real estate costs, the high cost of healthcare, and rapidly increasing credit card debt feel inescapable due to both the critical thinking and the collective capital needed to solve these challenges. At the same time, the very richest in our society continue to accumulate wealth at record pace. via Infographic Journal https://ift.tt/2LtQepB
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yesterday by leconeyc
24 Fun Bitcoin Facts & Figures That Will Make Your Head Spin [Infographic]
24 Fun Bitcoin Facts & Figures That Will Make Your Head Spin September 19, 2018 at 11:28AM https://ift.tt/2NpmnAE You have likely heard of the most famous among the cryptocurrencies "Bitcoin", but did you know that it was not the first cryptocurrency? The first cryptocurrency was in fact "Digicash" and was around a full ten years before the birth of Bitcoin. This infographic looks at Bitcoin and the weird and wonderful facts and figures surrounding it. via Infographic Journal https://ift.tt/2LtQepB
iftt  All  Feeds  Statistics  EVC 
yesterday by leconeyc
[1809.02512] Multi-level hypothesis testing for populations of heterogeneous networks
"In this work, we consider hypothesis testing and anomaly detection on datasets where each observation is a weighted network. Examples of such data include brain connectivity networks from fMRI flow data, or word co-occurrence counts for populations of individuals. Current approaches to hypothesis testing for weighted networks typically requires thresholding the edge-weights, to transform the data to binary networks. This results in a loss of information, and outcomes are sensitivity to choice of threshold levels. Our work avoids this, and we consider weighted-graph observations in two situations, 1) where each graph belongs to one of two populations, and 2) where entities belong to one of two populations, with each entity possessing multiple graphs (indexed e.g. by time). Specifically, we propose a hierarchical Bayesian hypothesis testing framework that models each population with a mixture of latent space models for weighted networks, and then tests populations of networks for differences in distribution over components. Our framework is capable of population-level, entity-specific, as well as edge-specific hypothesis testing. We apply it to synthetic data and three real-world datasets: two social media datasets involving word co-occurrences from discussions on Twitter of the political unrest in Brazil, and on Instagram concerning Attention Deficit Hyperactivity Disorder (ADHD) and depression drugs, and one medical dataset involving fMRI brain-scans of human subjects. The results show that our proposed method has lower Type I error and higher statistical power compared to alternatives that need to threshold the edge weights. Moreover, they show our proposed method is better suited to deal with highly heterogeneous datasets."
to:NB  to_read  re:network_differences  network_data_analysis  statistics  hypothesis_testing  functional_connectivity  neuroscience  neville.jennifer 
yesterday by cshalizi
[0802.0021] Time series analysis via mechanistic models
"The purpose of time series analysis via mechanistic models is to reconcile the known or hypothesized structure of a dynamical system with observations collected over time. We develop a framework for constructing nonlinear mechanistic models and carrying out inference. Our framework permits the consideration of implicit dynamic models, meaning statistical models for stochastic dynamical systems which are specified by a simulation algorithm to generate sample paths. Inference procedures that operate on implicit models are said to have the plug-and-play property. Our work builds on recently developed plug-and-play inference methodology for partially observed Markov models. We introduce a class of implicitly specified Markov chains with stochastic transition rates, and we demonstrate its applicability to open problems in statistical inference for biological systems. As one example, these models are shown to give a fresh perspective on measles transmission dynamics. As a second example, we present a mechanistic analysis of cholera incidence data, involving interaction between two competing strains of the pathogen Vibrio cholerae."
in_NB  statistics  time_series  simulation  to_teach:data_over_space_and_time 
yesterday by cshalizi

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