scholarly journals Conditions for rapid mixing of parallel and simulated tempering on multimodal distributions

2009 ◽  
Vol 19 (2) ◽  
pp. 617-640 ◽  
Author(s):  
Dawn B. Woodard ◽  
Scott C. Schmidler ◽  
Mark Huber
Keyword(s):  
Rapid Mixing ◽  
Multimodal Distributions ◽  
Simulated Tempering

scholarly journals ‘Statistical Irreproducibility’ Does Not Improve with Larger Sample Size: How to Quantify and Address Disease Data Multimodality in Human and Animal Research

2021 ◽  
Vol 11 (3) ◽  
pp. 234
Author(s):  
Abigail R. Basson ◽  
Fabio Cominelli ◽  
Alexander Rodriguez-Palacios
Keyword(s):  
Sample Size ◽  
Data Visualization ◽  
Random Sampling ◽  
Intestinal Inflammation ◽  
Random Number Generation ◽  
Outcome Data ◽  
Multimodal Distributions ◽  
Disease Subtypes ◽  
Study Designs ◽  
Larger Sample

Poor study reproducibility is a concern in translational research. As a solution, it is recommended to increase sample size (N), i.e., add more subjects to experiments. The goal of this study was to examine/visualize data multimodality (data with >1 data peak/mode) as cause of study irreproducibility. To emulate the repetition of studies and random sampling of study subjects, we first used various simulation methods of random number generation based on preclinical published disease outcome data from human gut microbiota-transplantation rodent studies (e.g., intestinal inflammation and univariate/continuous). We first used unimodal distributions (one-mode, Gaussian, and binomial) to generate random numbers. We showed that increasing N does not reproducibly identify statistical differences when group comparisons are repeatedly simulated. We then used multimodal distributions (>1-modes and Markov chain Monte Carlo methods of random sampling) to simulate similar multimodal datasets A and B (t-test-p = 0.95; N = 100,000), and confirmed that increasing N does not improve the ‘reproducibility of statistical results or direction of the effects’. Data visualization with violin plots of categorical random data simulations with five-integer categories/five-groups illustrated how multimodality leads to irreproducibility. Re-analysis of data from a human clinical trial that used maltodextrin as dietary placebo illustrated multimodal responses between human groups, and after placebo consumption. In conclusion, increasing N does not necessarily ensure reproducible statistical findings across repeated simulations due to randomness and multimodality. Herein, we clarify how to quantify, visualize and address disease data multimodality in research. Data visualization could facilitate study designs focused on disease subtypes/modes to help understand person–person differences and personalized medicine.

scholarly journals Safe Motion Planning against Multimodal Distributions based on a Scenario Approach

2021 ◽  
pp. 1-1
Author(s):  
Heejin Ahn ◽  
Colin Chen ◽  
Ian M. Mitchell ◽  
Maryam Kamgarpour
Keyword(s):  
Motion Planning ◽  
Multimodal Distributions ◽  
Scenario Approach

The Brazilian Reliability Test and Micromechanical Modelling for Channelled Cylinders of Multiphased Porous Ceramics

2007 ◽  
Vol 280-283 ◽  
pp. 1731-1738 ◽  
Author(s):  
Frédéric Osterstock ◽  
Ioannis St. Doltsinis ◽  
Olivier Vansse
Keyword(s):  
Mechanical Model ◽  
Weibull Modulus ◽  
Porous Ceramics ◽  
Brazilian Test ◽  
Micromechanical Modelling ◽  
Multimodal Distributions ◽  
The Mean ◽  
Model Structures ◽  
Good Homogeneity ◽  
Equal Thickness

Channelled hollow ceramic cylinders have been sliced into discs of equal thickness and submitted to an adapted diametral compression, or brazilian, test such as to evaluate their reliability. The mean Weibull modulus, of m » 18, is representative of a rather good homogeneity of the ceramic material. The shapes of the distributions reveal a probable multimodality. This is analyzed in superimposing possible unimodal distributions of given characteristic value, Weibull modulus and number of items, and comparing to the experimental plot. Iterative modifications are made until a convincing superposition is attained. Complementary numerical simulations on “thermomechanically equivalent microstructures” have been created on the computer observing actual stereological data. The micro-mechanical model accounts for cracking of grain interfaces until specimen separation. Weibull plots for model structures under pore pressure suggest multimodal distributions with moduli ranging as in the measurements. The larger scatter at higher rupture pressures may indicate a varying degree of quasi-brittleness.

scholarly journals Rapid mixing of sub-microlitre drops by magnetic micro-stirring

Lab on a Chip ◽  
2011 ◽  
Vol 11 (19) ◽  
pp. 3313 ◽  
Author(s):  
Dirk De Bruyker ◽  
Michael I. Recht ◽  
Ali Asgar S. Bhagat ◽  
Francisco E. Torres ◽  
Alan G. Bell ◽  
...  
Keyword(s):  
Rapid Mixing
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