Regressions

Regression Indicators

Reference

Indicators.mlrMethod.
mlr(y::Array{T}; n::Int64=10)::Array{T} where {T<:Real}

Moving linear regression predictions

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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

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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)

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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

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Indicators.mlr_lbMethod.
mlr_lb(y::Array{T}; n::Int64=10, se::T=2.0)::Array{T} where {T<:Real}

Moving linear regression lower bound

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Indicators.mlr_rsqMethod.
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

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Indicators.mlr_seMethod.
mlr_se(y::Array{T}; n::Int64=10)::Array{T} where {T<:Real}

Moving linear regression standard errors

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mlr_slope(y::Array{T}; n::Int64=10, x::Array{T}=collect(1.0:n))::Array{T} where {T<:Real}

Moving linear regression slope

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Indicators.mlr_ubMethod.
mlr_ub(y::Array{T}; n::Int64=10, se::T=2.0)::Array{T} where {T<:Real}

Moving linear regression upper bound

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