STY: cosmetic changes

.gitignore

@@ -1,3 +1,4 @@
 .ipynb_checkpoints/
 *.DS_Store
 *.cov
+*.juliahistory

src/markov_approx.jl

@@ -10,8 +10,8 @@ References
 
 http://quant-econ.net/finite_markov.html
 =#
-norm_cdf{T <: Real}(x::T) = 0.5 * erfc(-x/sqrt(2))
-norm_cdf{T <: Real}(x::Array{T}) = 0.5 .* erfc(-x./sqrt(2))
+std_norm_cdf{T <: Real}(x::T) = 0.5 * erfc(-x/sqrt(2))
+std_norm_cdf{T <: Real}(x::Array{T}) = 0.5 .* erfc(-x./sqrt(2))
 
 
 function tauchen(N::Int64, ρ::Real, σ::Real, μ::Real=0.0, n_std::Int64=3)
@@ -59,21 +59,21 @@ function tauchen(N::Int64, ρ::Real, σ::Real, μ::Real=0.0, n_std::Int64=3)
  Π = zeros(N, N)
  for row = 1:N
  # Do end points first
- Π[row, 1] = norm_cdf((y[1] - ρ*y[row] + d/2) / σ)
- Π[row, N] = 1 - norm_cdf((y[N] - ρ*y[row] - d/2) / σ)
+ Π[row, 1] = std_norm_cdf((y[1] - ρ*y[row] + d/2) / σ)
+ Π[row, N] = 1 - std_norm_cdf((y[N] - ρ*y[row] - d/2) / σ)
 
  # fill in the middle columns
  for col = 2:N-1
- Π[row, col] = (norm_cdf((y[col] - ρ*y[row] + d/2) / σ) -
- norm_cdf((y[col] - ρ*y[row] - d/2) / σ))
+ Π[row, col] = (std_norm_cdf((y[col] - ρ*y[row] + d/2) / σ) -
+ std_norm_cdf((y[col] - ρ*y[row] - d/2) / σ))
  end
  end
 
  # NOTE: I need to shift this vector after finding probabilities
- # because when finding the probabilities I use a function norm_cdf
- # that assumes its input argument is distributed N(0, 1). After
- # adding the mean E[y] is no longer 0, so I would be passing
- # elements with the wrong distribution.
+ # because when finding the probabilities I use a function
+ # std_norm_cdf that assumes its input argument is distributed
+ # N(0, 1). After adding the mean E[y] is no longer 0, so
+ # I would be passing elements with the wrong distribution.
  #
  # It is ok to do after the fact because adding this constant to each
  # term effectively shifts the entire distribution. Because the
@@ -83,6 +83,7 @@ function tauchen(N::Int64, ρ::Real, σ::Real, μ::Real=0.0, n_std::Int64=3)
  # I could have shifted it before, but then I would need to evaluate
  # the cdf with a function that allows the distribution of input
  # arguments to be [μ/(1 - ρ), 1] instead of [0, 1]
+
  y .+= μ / (1 - ρ) # center process around its mean (wbar / (1 - rho))
 
  return y, Π
@@ -137,6 +138,8 @@ function rouwenhorst(N::Int, ρ::Real, σ::Real, μ::Real=0.0)
 
  ψ = sqrt(N-1) * σ_y
  w = linspace(-ψ, ψ, N)
+
  w .+= μ / (1 - ρ) # center process around its mean (wbar / (1 - rho))
+
  return w, Θ
 end

src/mc_tools.jl

@@ -191,4 +191,4 @@ function mc_sample_path!(mc::MarkovChain, samples::Vector)
  length(samples) < 2 &&
  throw(ArgumentError("samples vector must have length greater than 2"))
  samples = mc_sample_path(mc,samples[1],length(samples)-1)
-end
+end