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Not a Research Blog | Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science &…what else is there?

Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science &...what else is there?

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Not a Research Blog | Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science &…what else is there? | omaclaren.com Reviews
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Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science &...what else is there?
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Not a Research Blog | Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science &…what else is there? | omaclaren.com Reviews

https://omaclaren.com

Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science &...what else is there?

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1

Recent reading: a miscellany of slightly obscure things | Not a Research Blog

https://omaclaren.com/2016/02/14/recent-reading-a-miscellany-of-slightly-obscure-things

Not a Research Blog. Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science & #8230;what else is there? Recent reading: a miscellany of slightly obscure things. Sometimes I forget which things I’m currently reading (i.e. dipping in and out of). So, here are a few notes, mainly to myself and mainly about books and more obscure sources than the usual current research papers. Related to the above, a few books (and a paper or two) on ...

2

Closure: objective and subjective, truth and approximation | Not a Research Blog

https://omaclaren.com/2015/10/13/closure-objective-and-subjective-truth-and-approximation

Not a Research Blog. Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science & #8230;what else is there? Closure: objective and subjective, truth and approximation. A sketch of a few thoughts on ‘objective’ vs ‘subjective’ and ‘truth’ vs ‘approximation’ in the context of what I’ve been calling ‘ model closure. 8216; Taking a roughly/informally category theory perspective. Includes more discussion of how the. As well as issues of.

3

Hierarchical Bayes | Not a Research Blog

https://omaclaren.com/2016/09/01/hierarchical-bayes

Not a Research Blog. Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science & #8230;what else is there? This is ‘Not a Research Blog’, but nevertheless some thoughts on, and application of, hierarchical Bayes that are related to what I’ve been posting about here can be found in my recent preprint:. A hierarchical Bayesian framework for understanding the spatiotemporal dynamics of the intestinal epithelium. September 1, 2016. On Is...

4

Uncategorized | Not a Research Blog

https://omaclaren.com/category/uncategorized

Not a Research Blog. Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science & #8230;what else is there? 8230;can be found here: https:/ github.com/omaclaren/open-learning-material. Like all such material much of it is either shamelessly (or shamefully! Also, this material should be assumed to contain at least some gross errors or major misconceptions! This entry was posted in Uncategorized. March 8, 2017. Converting sample statist...

5

Linear or nonlinear with respect to what? | Not a Research Blog

https://omaclaren.com/2016/03/29/linear-or-nonlinear-with-respect-to-what

Not a Research Blog. Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science & #8230;what else is there? Linear or nonlinear with respect to what? It’s my understanding that a PDE is linear if we can. Write it in the form. Is a linear differential operator. If we are given a PDE that looks like. For some differential operator A. And asked to show that the PDE is. I can (probably) show that A. For example the operator A. As you&#821...

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When does Bayes do the job? - Statistical Modeling, Causal Inference, and Social Science

http://andrewgelman.com/2015/08/06/when-does-bayes-do-the-job

Statistical Modeling, Causal Inference, and Social Science. Laquo; How Hamiltonian Monte Carlo works. The secret to making a successful conference presentation. When does Bayes do the job? On 6 August 2015, 9:57 am. I recall that you have also stressed this issue, and I’d like to acknowledge that. Do you have pointers to a few of your papers where you explicitly mention this? Ideally I would just take a quotation. Which I absolutely love. Then there’s this paper. Here’s a quote from that paper:. The next...

models.street-artists.org models.street-artists.org

My Company | Models Of Reality

http://models.street-artists.org/my-company

Engineering, Science, and Society. This blog represents my personal communications about science, engineering, social sciences, and how mathematical modeling fits into the picture. Professionally, I am now running a consulting company Lakeland Applied Sciences LLC. Where I put my mathematical modeling skills to work, in order to help people understand and develop new ideas into productive business opportunities. Get posts via RSS feed. Rdquo; May 4, 10:41. Ldquo; Very cool! Rdquo; May 4, 10:25. Ldquo; Sm...

andrewgelman.com andrewgelman.com

How to solve the Post Office’s problems? - Statistical Modeling, Causal Inference, and Social Science

http://andrewgelman.com/2011/09/how-to-solve-the-post-office’s-problems

Statistical Modeling, Causal Inference, and Social Science. Laquo; Hipmunk FAIL: Graphics without content is not enough. The difference between significant and not significant…. How to solve the Post Office’s problems? On 8 September 2011, 9:30 am. Felix Salmon offers some suggestions. For some background, see this news article. By Steven Greenhouse.). September 8, 2011 at 10:13 am. Get into financial services? Banks don’t like competition, even for firms likely to start by serving customers they d...

andrewgelman.com andrewgelman.com

Born-open data - Statistical Modeling, Causal Inference, and Social Science

http://andrewgelman.com/2015/06/17/born-open-data

Statistical Modeling, Causal Inference, and Social Science. Laquo; Stan workshops at UCLA (6/23) and UCI (6/24). You can crush us, you can bruise us, yes, even shoot us, but oh—not a pie chart! On 17 June 2015, 11:36 am. And here’s the crux:. On the other hand, surprisingly, very few of our collective data are open! Say it again, brother:. What about current practice? Here’s one of my experiences with data-on-request:. I guess the Solomon-like compromise would’ve been to saw the dataset in half. On the s...

models.street-artists.org models.street-artists.org

Who am I? | Models Of Reality

http://models.street-artists.org/who-am-i

Engineering, Science, and Society. The short version is that I am a PhD student in Civil Engineering, studying mathematical methods for modeling materials and for analyzing risk. The long version may be more interesting:. Who now mainly works on hacking Lisp code. I spent several years in the early days of serious web application development ( 2001) trying to build a mouse genetics management database. I hated web development. My passion is for modeling. I then worked for Jax Kneppers Associates, a foren...

andrewgelman.com andrewgelman.com

A Bayesian model for an increasing function, in Stan! - Statistical Modeling, Causal Inference, and Social Science

http://andrewgelman.com/2013/11/22/bayesian-model-increasing-function-stan

Statistical Modeling, Causal Inference, and Social Science. Laquo; Hidden dangers of noninformative priors. Tables figures yet again. A Bayesian model for an increasing function, in Stan! On 22 November 2013, 9:42 am. Following up on yesterday’s post, here’s David Chudzicki’s story. With graphs and Stan/R code! Of how he fit a model for an increasing function (“isotonic regression”). Chudzicki writes:. One thing I like about this example is that it’s. Filed under Bayesian Statistics. Reply to this comment.

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Food Science | Models Of Reality

http://models.street-artists.org/category/food-science

Engineering, Science, and Society. Posts from the ‘Food Science’ Category. A Grapefruit A Day. brings the doctor to stay? Norovirus, and Bleach Dilution For Sanitization. Quick Comment on the 45 minute Turkey. Reducing Turkey Cooking Time. My 2010 Turkey data. Cooking Turkeys: I need MORE DATA! DHA and Fish Oil Use in Pregnancy. Babies, or Adults, Sunlight, and Vitamin D. Biological feedback and breast milk: an example of simple models being wrong. Laquo; Older Entries. Get posts via RSS feed. Ldquo; Smo...

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Perry Family of Kershaw and Lancaster Counties South Carolina. Perry 1690 - 1841. Benjamin and James Perry of Virginia. Liberty Hill Day 1. Liberty Hill houses Day 1. Henry (Hal) Brown Perry and Amelia Ragsdale Perry. Henry (Hal B) Brown Perry,Jr. Jane Curry Perry Carlisle. Anna Mae Perry Wood. Margaret (Margie) Elizabeth Perry Boren. Bessie (Betty) Amelia Perry Kirk. William Ragsdale (Bill) Perry. Bessie Perry Hines and Cornelia Perry Scott. Welcome to the Perry Family site.

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The Online Medieval & Classical Library

The Online Medieval and Classical Library (OMACL) is a collection of some of the most important literary works of Classical and Medieval civilization. Get your OMACL gear. And let your love of classical and medieval literature show! Site created by Douglas B. Killings and Roy Tennant, maintained by Roy Tennant. On behalf of the academic community. The photo of one of the Lady and the Unicorn. Tapestries (c. 1511) is used by permission of FreeLargePhotos.com. Real Estate Marketing Services.

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Not a Research Blog | Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science &…what else is there?

Not a Research Blog. Distracting thoughts on mathematics, modelling, simulation, inference, epistemology, causality, statistics, data science, science & #8230;what else is there? Substitutional vs objectual quantification. The interpretation of logical quantifiers such as ‘. 8216; and ‘. 8216; and the associated. But didn’t pay much attention. Is a central figure here – e.g. his famous (within philosophy, anyway) saying ‘. To be is to be the value of a variable. 8216; concerns this issue. P(x), obtained ...

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