Module: Statsample::GLM

Includes:
VectorShorthands
Defined in:
lib/statsample-glm/glm.rb,
lib/statsample-glm/version.rb,
lib/statsample-glm/glm/base.rb,
lib/statsample-glm/glm/normal.rb,
lib/statsample-glm/glm/probit.rb,
lib/statsample-glm/glm/poisson.rb,
lib/statsample-glm/glm/logistic.rb,
lib/statsample-glm/glm/mle/base.rb,
lib/statsample-glm/glm/irls/base.rb,
lib/statsample-glm/glm/mle/normal.rb,
lib/statsample-glm/glm/mle/probit.rb,
lib/statsample-glm/glm/irls/poisson.rb,
lib/statsample-glm/glm/mle/logistic.rb,
lib/statsample-glm/glm/irls/logistic.rb

Defined Under Namespace

Modules: IRLS, MLE Classes: Base, Logistic, Normal, Poisson, Probit

Constant Summary collapse

VERSION = 
"0.2.1"

Class Method Summary collapse

Class Method Details

.compute(data_set, dependent_column, method, opts = {}) ⇒ Object

Generalized linear models

Parameters

  • x = model matrix

  • y = response vector

Usage

require 'statsample-glm'
x1 = Daru::Vector.new([0.537322309644812,-0.717124209978434,-0.519166718891331,0.434970973986765,-0.761822002215759,1.51170030921189,0.883854199811195,-0.908689798854196,1.70331977539793,-0.246971150634099,-1.59077593922623,-0.721548040910253,0.467025703920194,-0.510132788447137,0.430106510266798,-0.144353683251536,-1.54943800728303,0.849307651309298,-0.640304240933579,1.31462478279425,-0.399783455165345,0.0453055645017902,-2.58212161987746,-1.16484414309359,-1.08829266466281,-0.243893919684792,-1.96655661929441,0.301335373291024,-0.665832694463588,-0.0120650855753837,1.5116066367604,0.557300353673344,1.12829931872045,0.234443748015922,-2.03486690662651,0.275544751380246,-0.231465849558696,-0.356880153225012,-0.57746647541923,1.35758352580655,1.23971669378224,-0.662466275100489,0.313263561921793,-1.08783223256362,1.41964722846899,1.29325100940785,0.72153880625103,0.440580131022748,0.0351917814720056, -0.142353224879252])
x2 = Daru::Vector.new([-0.866655707911859,-0.367820249977585,0.361486610435,0.857332626245179,0.133438466268095,0.716104533073575,1.77206093023382,-0.10136697295802,-0.777086491435508,-0.204573554913706,0.963353531412233,-1.10103024900542,-0.404372761837392,-0.230226345183469,0.0363730246866971,-0.838265540390497,1.12543549657924,-0.57929175648001,-0.747060244805248,0.58946979365152,-0.531952663697324,1.53338594419818,0.521992029051441,1.41631763288724,0.611402316795129,-0.518355638373296,-0.515192557101107,-0.672697937866108,1.84347042325327,-0.21195540664804,-0.269869371631611,0.296155694010096,-2.18097898069634,-1.21314663927206,1.49193669881581,1.38969280369493,-0.400680808117106,-1.87282814976479,1.82394870451051,0.637864732838274,-0.141155946382493,0.0699950644281617,1.32568550595165,-0.412599258349398,0.14436832227506,-1.16507785388489,-2.16782049922428,0.24318371493798,0.258954871320764,-0.151966534521183])
y_pois = Daru::Vector.new([1,2,1,3,3,1,10,1,1,2,15,0,0,2,1,2,18,2,1,1,1,8,18,13,7,1,1,0,26,0,2,2,0,0,25,7,0,0,21,0,0,1,5,0,3,0,0,1,0,0])
x=Daru::DataFrame.new({:x1 => x1,:x2 => x2, :y => y_pois})
obj = Statsample::GLM.compute(x, :y, :poisson, {algorithm: :irls})
#=> Logistic Regression object

Returns

GLM object for given method.



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# File 'lib/statsample-glm/glm.rb', line 27

def self.compute(data_set, dependent_column, method, opts={})
  opts[:method] = method

  # TODO: Remove this const_get jugaad after 1.9.3 support is removed.

  Kernel.const_get("Statsample").const_get("GLM").const_get("#{method.capitalize}").new data_set, 
    dependent_column, opts
end