Regression Indicators
Reference
Indicators.mlr
— Method.mlr(y::Array{T}; n::Int64=10)::Array{T} where {T<:Real}
Moving linear regression predictions
Indicators.mlr_bands
— Method.mlr_bands(y::Array{T}; n::Int64=10, se::T=2.0)::Matrix{T} where {T<:Real}
Moving linear regression bands
Output:
Column 1: Lower bound
Column 2: Regression estimate
Column 3: Upper bound
Indicators.mlr_beta
— Method.mlr_beta(y::Array{T}; n::Int64=10, x::Array{T}=collect(1.0:n))::Matrix{T} where {T<:Real}
Moving linear regression intercept (column 1) and slope (column 2)
Indicators.mlr_intercept
— Method.mlr_intercept(y::Array{T}; n::Int64=10, x::Array{T}=collect(1.0:n))::Array{T} where {T<:Real}
Moving linear regression y-intercept
Indicators.mlr_lb
— Method.mlr_lb(y::Array{T}; n::Int64=10, se::T=2.0)::Array{T} where {T<:Real}
Moving linear regression lower bound
Indicators.mlr_rsq
— Method.mlr_rsq(y::Array{T}; n::Int64=10, adjusted::Bool=false)::Array{T} where {T<:Real}
Moving linear regression R-squared or adjusted R-squared
Indicators.mlr_se
— Method.mlr_se(y::Array{T}; n::Int64=10)::Array{T} where {T<:Real}
Moving linear regression standard errors
Indicators.mlr_slope
— Method.mlr_slope(y::Array{T}; n::Int64=10, x::Array{T}=collect(1.0:n))::Array{T} where {T<:Real}
Moving linear regression slope
Indicators.mlr_ub
— Method.mlr_ub(y::Array{T}; n::Int64=10, se::T=2.0)::Array{T} where {T<:Real}
Moving linear regression upper bound