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Explore What Others Are Building

Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.

There is much we can learn from the development of qualitative relationships models though once we begin to ask questions like how long, how much, when, etc., a qualitative most is not likely to be of much use. The following video demonstrates how, in a very simple goal-seeking structure with delay,
Goal Seeking With Delay
There is much we can learn from the development of qualitative relationships models though once we begin to ask questions like how long, how much, when, etc., a qualitative most is not likely to be of much use. The following video demonstrates how, in a very simple goal-seeking structure with delay, depending on the delay, it can be almost impossible to intuit the implications of the interactions with any level of accuracy. The difficulty arises essentially from operating with outdated data. See also Archetypes.
Goal Seeking with Delay
Gene Bellinger
29
This is a first example of a simple SIR (Susceptible, Infected, Recovered) model. There are three pools of individuals: those who are infected (without them, no disease!), the pool of those who are at risk (susceptible), and the recovered -- who may lose their immunity and become susceptible again
Math Modeling Mat375 SIR
This is a first example of a simple SIR (Susceptible, Infected, Recovered) model.

There are three pools of individuals: those who are infected (without them, no disease!), the pool of those who are at risk (susceptible), and the recovered -- who may lose their immunity and become susceptible again.

A comparable model in Mathematica is available at
http://www.nku.edu/~longa/classes/2018spring/mat375/mathematica/SIRModel.nb

A Simple SIR (Susceptible, Infected, Recovered) Example
Andrew E Long
130
WIP Summary of Klein and Kahneman's American Psychologist 2009 article 
Explanation Klein Kahneman Inference Inquiry Macrocognition Rationality
WIP Summary of Klein and Kahneman's American Psychologist 2009 article 
Intuitive Expertise
Geoff McDonnell
2 weeks ago
This model explores the relationships between transaction volume, rewards, and stake-pool profitability on Cardano. See  https://leios.cardano-scaling.org/ for more information.
Cardano blockchain
This model explores the relationships between transaction volume, rewards, and stake-pool profitability on Cardano. See https://leios.cardano-scaling.org/ for more information.
Cardano Throughput v0.2
Brian Bush
3 weeks ago
Simulating Hyperinflation for 3650 days. If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings.  We don't show the details of the central bank buying bonds here,
Money Inflation Hyperinflation Finance Economics
Simulating Hyperinflation for 3650 days.

If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings.  We don't show the details of the central bank buying bonds here, just the net results.

See blog at http://howfiatdies.blogspot.com for more on hyperinflation, including a hyperinflation FAQ.
Hyperinflation Simulation
Vincent Cate
13
STEM-SM combines a simple ecosystem model (modified version of VSEM; Hartig et al. 2019) with a soil moisture model (Guswa et al. (2002) leaky bucket model). Outputs from the soil moisture model influence ecosystem dynamics in three ways.  (1) The ratio of actual transpiration to maximum evapotran
GEG5224 Ecosystem Ecology Environment Carbon Productivity Decomposition Evapotranspiration Water Soil moisture
STEM-SM combines a simple ecosystem model (modified version of VSEM; Hartig et al. 2019) with a soil moisture model (Guswa et al. (2002) leaky bucket model). Outputs from the soil moisture model influence ecosystem dynamics in three ways. 
(1) The ratio of actual transpiration to maximum evapotranspiration (T/ETmax) modifies gross primary productivity (GPP).
(2) Degree of saturation of the soil (Sd) modifies the rate of soil heterotrophic respiration.
(3) Water limitation of GPP (by T/ETmax) and of soil nutrient availability (approximated by Sd) combine with leaf area limitation (approximated by fraction of incident photosynthetically-active radiation that is absorbed) to modify the allocation of net primary productivity to aboveground and belowground parts of the vegetation.

Ecosystem dynamics in turn influence flows of water in to and out of the soil moisture stock. The size of the aboveground biomass stock determines fractional vegetation cover, which modifies interception, soil evaporation and transpiration by plants.

References:
Guswa, A.J., Celia, M.A., Rodriguez-Iturbe, I. (2002) Models of soil moisture dynamics in ecohydrology: a comparative study. Water Resources Research 38, 5-1 - 5-15.

Hartig, F., Minunno, F., and Paul, S. (2019). BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics. R package version 0.1.7. https://CRAN.R-project.org/package=BayesianTools

Simple Terrestrial Ecosystem Model - Soil Moisture (STEM-SM)
Lisa Belyea
159 3 weeks ago