Is it possible to do a poisson distribution with the probabilities based on integers? - probability

Question

Working within Solidity and the Ethereum EVM and Decimals don't exist. Is there a way I could mathematically still create a Poisson distribution using integers ? it doesnt have to be perfect, i.e rounding or losing some digits may be acceptable.

Answer 1

Let me preface by stating that what follows is not going to be (directly) helpful to you with etherium/solidity. However, it produces probability tables that you might be able to use for your work.
I ended up intrigued by the question of how accurate you could be in expressing the Poisson probabilities as rationals, so I put together the following script in Ruby to try things out:
def rational_poisson(lmbda)
Hash.new.tap do |h| # create a hash and pass it to this block as 'h'.
# Make all components of the calculations rational to allow
# cancellations to occur wherever possible when dividing
e_to_minus_lambda = Math.exp(-lmbda).to_r
factorial = 1r
lmbda = lmbda.to_r
power = 1r
(0...).each do |x|
unless x == 0
power *= lmbda
factorial *= x
end
value = (e_to_minus_lambda / factorial) * power
# the following double inversion/conversion bounds the result
# by the significant bits in the mantissa of a float
approx = Rational(1, (1 / value).to_f)
h[x] = approx
break if x > lmbda && approx.numerator <= 1
end
end
end
if __FILE__ == $PROGRAM_NAME
lmbda = (ARGV.shift || 2.0).to_f # read in a lambda (defaults to 2.0)
pmf = rational_poisson(lmbda) # create the pmf for a Poisson with that lambda
pmf.each { |key, value| puts "p(#{key}) = #{value} = #{value.to_f}" }
puts "cumulative error = #{1.0 - pmf.values.inject(&:+)}" # does it sum to 1?
end
Things to know as you glance through the code. Appending .to_r to a value or expression converts it to a rational, i.e., a ratio of two integers; values with an r suffix are rational constants; and (0...).each is an open-ended iterator which will loop until the break condition is met.
That little script produces results such as:
localhost:pjs$ ruby poisson_rational.rb 1.0
p(0) = 2251799813685248/6121026514868073 = 0.36787944117144233
p(1) = 2251799813685248/6121026514868073 = 0.36787944117144233
p(2) = 1125899906842624/6121026514868073 = 0.18393972058572117
p(3) = 281474976710656/4590769886151055 = 0.061313240195240384
p(4) = 70368744177664/4590769886151055 = 0.015328310048810096
p(5) = 17592186044416/5738462357688819 = 0.003065662009762019
p(6) = 1099511627776/2151923384133307 = 0.0005109436682936699
p(7) = 274877906944/3765865922233287 = 7.299195261338141e-05
p(8) = 34359738368/3765865922233287 = 9.123994076672677e-06
p(9) = 67108864/66196861914257 = 1.0137771196302974e-06
p(10) = 33554432/330984309571285 = 1.0137771196302975e-07
p(11) = 33554432/3640827405284135 = 9.216155633002704e-09
p(12) = 4194304/5461241107926203 = 7.68012969416892e-10
p(13) = 524288/8874516800380079 = 5.907792072437631e-11
p(14) = 32768/7765202200332569 = 4.2198514803125934e-12
p(15) = 256/909984632851473 = 2.8132343202083955e-13
p(16) = 16/909984632851473 = 1.7582714501302472e-14
p(17) = 1/966858672404690 = 1.0342773236060278e-15
cumulative error = 0.0