Monte_Carlo_simulations any alternate solution for VAR
from scipy.stats import poisson, lognorm # Function to calculate VaR for Net Loss using Monte Carlo def calculate_net_loss_var(frequency_lambda, severity_shape, severity_scale, severity_loc, confidence_level=0.999, n_simulations=10000): simulated_event_counts = poisson.rvs(mu=frequency_lambda, size=n_simulations) simulated_loss_amounts = lognorm.rvs(s=severity_shape, loc=severity_loc, scale=severity_scale, size=n_simulations) total_losses = simulated_event_counts * simulated_loss_amounts var_value = np.percentile(total_losses, confidence_level * 100) return var_value # Function to calculate VaR for Event Counts using […]
How to implement a simulation pattern for a repository?
Let’s say I have a repository of functions. These functions work with business objects within a database, CMS or other third party API. For example, my repository interacts with virtual files and documents in a document management system. I want to be able to implement a simulation mode in my repository such that when I execute commands, I want to see the result of it without it actually doing anything. This is to reduce the risk of someone executing a series of commands in my repository and doing something dangerous. I want them to first see the output and confirm before executing.
Is there any better approach to shortest path finding within a (vehicular) traffic network?
Dear fellow programmers,
Evaluating mean and std as simulations are added
I have simulations that evaluate a certain value X. I run the simulations several times and save the value of X in a vector V. When all the runs have finished I evaluate the mean and standard deviation for the vector V.
How would I combine ‘Command’ and ‘Composite’ to simulate a time delay?
As a learning exercise (I am not in school – just an old guy trying to learn something new), I am trying to write a logic gate simulation that incorporates propagation delay. The user should also be able to group gates together to create higher-level objects.
Algorithm to Find the Aggregate Mass of “Granola Bar”-Like Structures?
I’m a planetary science researcher and one project I’m working on is N-body simulations of Saturn’s rings. The goal of this particular study is to watch as particles clump together under their own self-gravity and measure the aggregate mass of the clumps versus the mean velocity of all particles in the cell. We’re trying to figure out if this can explain some observations made by the Cassini spacecraft during the Saturnian summer solstice when large structures were seen casting shadows on the nearly edge-on rings. Below is a screenshot of what any given timestep looks like. (Each particle is 2 m in diameter and the simulation cell itself is around 700 m across.)
Algorithm to Find the Aggregate Mass of “Granola Bar”-Like Structures?
I’m a planetary science researcher and one project I’m working on is N-body simulations of Saturn’s rings. The goal of this particular study is to watch as particles clump together under their own self-gravity and measure the aggregate mass of the clumps versus the mean velocity of all particles in the cell. We’re trying to figure out if this can explain some observations made by the Cassini spacecraft during the Saturnian summer solstice when large structures were seen casting shadows on the nearly edge-on rings. Below is a screenshot of what any given timestep looks like. (Each particle is 2 m in diameter and the simulation cell itself is around 700 m across.)
Algorithm to Find the Aggregate Mass of “Granola Bar”-Like Structures?
I’m a planetary science researcher and one project I’m working on is N-body simulations of Saturn’s rings. The goal of this particular study is to watch as particles clump together under their own self-gravity and measure the aggregate mass of the clumps versus the mean velocity of all particles in the cell. We’re trying to figure out if this can explain some observations made by the Cassini spacecraft during the Saturnian summer solstice when large structures were seen casting shadows on the nearly edge-on rings. Below is a screenshot of what any given timestep looks like. (Each particle is 2 m in diameter and the simulation cell itself is around 700 m across.)
Algorithm to Find the Aggregate Mass of “Granola Bar”-Like Structures?
I’m a planetary science researcher and one project I’m working on is N-body simulations of Saturn’s rings. The goal of this particular study is to watch as particles clump together under their own self-gravity and measure the aggregate mass of the clumps versus the mean velocity of all particles in the cell. We’re trying to figure out if this can explain some observations made by the Cassini spacecraft during the Saturnian summer solstice when large structures were seen casting shadows on the nearly edge-on rings. Below is a screenshot of what any given timestep looks like. (Each particle is 2 m in diameter and the simulation cell itself is around 700 m across.)
Algorithm to Find the Aggregate Mass of “Granola Bar”-Like Structures?
I’m a planetary science researcher and one project I’m working on is N-body simulations of Saturn’s rings. The goal of this particular study is to watch as particles clump together under their own self-gravity and measure the aggregate mass of the clumps versus the mean velocity of all particles in the cell. We’re trying to figure out if this can explain some observations made by the Cassini spacecraft during the Saturnian summer solstice when large structures were seen casting shadows on the nearly edge-on rings. Below is a screenshot of what any given timestep looks like. (Each particle is 2 m in diameter and the simulation cell itself is around 700 m across.)