FunctionSurvivalEstimationLibrary "FunctionSurvivalEstimation"
The Survival Estimation function, also known as Kaplan-Meier estimation or product-limit method, is a statistical technique used to estimate the survival probability of an individual over time. It's commonly used in medical research and epidemiology to analyze the survival rates of patients with different treatments, diseases, or risk factors.
What does it do?
The Survival Estimation function takes into account censored observations (i.e., individuals who are still alive at a certain point) and calculates the probability that an individual will survive beyond a specific time period. It's particularly useful when dealing with right-censoring, where some subjects are lost to follow-up or have not experienced the event of interest by the end of the study.
Interpretation
The Survival Estimation function provides a plot of the estimated survival probability over time, which can be used to:
1. Compare survival rates between different groups (e.g., treatment arms)
2. Identify patterns in the data that may indicate differences in mortality or disease progression
3. Make predictions about future outcomes based on historical data
4. In a trading context it may be used to ascertain the survival ratios of trading under specific conditions.
Reference:
www.global-developments.org
"Beyond GDP" ~ www.aeaweb.org
en.wikipedia.org
www.kdnuggets.com
survival_probability(alive_at_age, initial_alive)
Kaplan-Meier Survival Estimator.
Parameters:
alive_at_age (int) : The number of subjects still alive at a age.
initial_alive (int) : The Total number of initial subjects.
Returns: The probability that a subject lives longer than a certain age.
utility(c, l)
Captures the utility value from consumption and leisure.
Parameters:
c (float) : Consumption.
l (float) : Leisure.
Returns: Utility value from consumption and leisure.
welfare_utility(age, b, u, s)
Calculate the welfare utility value based age, basic needs and social interaction.
Parameters:
age (int) : Age of the subject.
b (float) : Value representing basic needs (food, shelter..).
u (float) : Value representing overall well-being and happiness.
s (float) : Value representing social interaction and connection with others.
Returns: Welfare utility value.
expected_lifetime_welfare(beta, consumption, leisure, alive_data, expectation)
Calculates the expected lifetime welfare of an individual based on their consumption, leisure, and survival probability over time.
Parameters:
beta (float) : Discount factor.
consumption (array) : List of consumption values at each step of the subjects life.
leisure (array) : List of leisure values at each step of the subjects life.
alive_data (array) : List of subjects alive at each age, the first element is the total or initial number of subjects.
expectation (float) : Optional, `defaut=1.0`. Expectation or weight given to this calculation.
Returns: Expected lifetime welfare value.
Estimation
Profit EstimateLibrary "profitestimate"
Simple profit Estimatr. Engages when Position != 0
and holds until posittion is na/0...
if position changes sizes, it will update automatically and adjust.
it has an input for comission to estmate exit fees
update_avgprice(_sizewas, _delta, _pricewas, _newprice)
Get a new Average position Price
Parameters:
_sizewas : (float) the position prior
_delta : (float) the order amount
_pricewas : (float) the prior price
_newprice : (float) the price of order
Returns: New Avg Price
amount(_position, _close, _commission, _leverage, _fullqty)
Position Net Profit Net Commission, automatic on/off if position != 0
Parameters:
_position : (float) position size (total or margin size)
_close
_commission : (float) % where (0.1 = 0.1%)
_leverage : (float) optional if leveraged, default 1x
_fullqty : (bool) if position entered is tottal trade size default is margin qty (1/lev)
Returns: quote value of profit
percent(_position, _close, _commission, _leverage, _fullqty)
Position Net Profit, automatic on/off if position != 0
Parameters:
_position : (float) position size (total or margin size)
_close
_commission : (float) % where (0.1 = 0.1%)
_leverage : (float) optional if leveraged, default 1x
_fullqty : (bool) if position entered is tottal trade size, default is margin qty (1/lev)
Returns: percentage profit (1% = 1)