minor changes, test, docs

docs/src/api.md

@@ -406,6 +406,13 @@ Metida.SpatialPowerD
 Metida.ScaledWeightedCov
 ```
 
+### Metida.ACOV
+
+```@docs
+Metida.ACOV
+```
+
+
 ### Metida.dof_contain
 
 ```@docs

src/Metida.jl

@@ -36,6 +36,7 @@ SPPOW, SpatialPower,
 SPGAU, SpatialGaussian, RawCoding,
 UN, Unstructured,
 CovarianceType,
+ACOV,
 fit, fit!, LMM, VarEffect, theta, logreml, m2logreml, m2logml, logml, thetalength, dof_satter, dof_contain, rankx, caic, lcontrast, typeiii, estimate, contrast,
 gmatrix, rmatrix, vmatrix!, responsename, nblocks, raneff,
 AbstractCovarianceType, AbstractCovmatMethod, MetidaModel,

src/rmat.jl

@@ -344,31 +344,69 @@ function rmat!(mx, θ, rz::AbstractMatrix, ::UN_, ::Int)
 end
 
 # ACOV (AR)
-function rmat!(mx, θ, ::AbstractMatrix, ::ACOV_{AR_}, ::Int)
+function rmat!(mx::AbstractMatrix{T}, θ, ::AbstractMatrix, ct::ACOV_{AR_}, ::Int) where T
     s  = size(mx, 1)
     ρ  = θ[1]
     if s > 1
         for n = 2:s
-            mxnn = sqrt(mx[n, n])
+            mxnn = mx[n, n]
             @inbounds @simd for m = 1:n-1
-                mxmm = sqrt(mx[m, m])
-                mx[m, n] += mxnn * mxmm * ρ ^ (n - m)
+                mxmm = mx[m, m]
+                mxmn = mx[m, n]
+                cov  = sqrt(mxnn * mxmm) * ρ ^ (n - m)
+                if ct.a != 0
+                    if ct.a == 1
+                        mxmn = zero(T)
+                    elseif ct.a == 2
+                        cov = zero(T)
+                    elseif ct.a == 3
+                        @warn "covariance have existed value!"
+                    elseif ct.a == 4
+                        @warn "covariance have existed value! replaced..."
+                        mxmn = zero(T)
+                    elseif ct.a == 5
+                        @warn "covariance have existed value! Save existed..."
+                        cov = zero(T)
+                    else
+                        error("covariance have existed value!")
+                    end
+                end
+                mx[m, n] = mxmn + cov
             end
         end
     end
     return mx
 end
 
 # ACOV (CS)
-function rmat!(mx, θ, ::AbstractMatrix, ::ACOV_{CS_}, ::Int)
+function rmat!(mx::AbstractMatrix{T}, θ, ::AbstractMatrix, ct::ACOV_{CS_}, ::Int) where T
     s  = size(mx, 1)
     ρ  = θ[1]
     if s > 1
         for n = 2:s
-            mxnn = sqrt(mx[n, n])
+            mxnn = mx[n, n]
             @inbounds @simd for m = 1:n-1
-                mxmm = sqrt(mx[m, m])
-                mx[m, n] += mxnn * mxmm * ρ 
+                mxmm = mx[m, m]
+                mxmn = mx[m, n]
+                cov  = sqrt(mxnn * mxmm) * ρ 
+                if ct.a != 0
+                    if ct.a == 1
+                        mxmn = zero(T)
+                    elseif ct.a == 2
+                        cov = zero(T)
+                    elseif ct.a == 3
+                        @warn "covariance have existed value!"
+                    elseif ct.a == 4
+                        @warn "covariance have existed value! replaced..."
+                        mxmn = zero(T)
+                    elseif ct.a == 5
+                        @warn "covariance have existed value! Save existed..."
+                        cov = zero(T)
+                    else
+                        error("covariance have existed value!")
+                    end
+                end
+                mx[m, n] = mxmn + cov
             end
         end
     end

src/vartypes.jl

@@ -406,10 +406,27 @@ const UN = Unstructured()
 
 
 """
-    ACOV(c)
+    ACOV(c, action = 0)
+
+!!! warning
+    Experimental
+    
+Augmented (adjusted) covariance. Add additional correlations to existed R-part of variance covariance matrix.
+Can be used with `AR` or `CS` types. 
+
+`action` if existed covariance not equal sero:
+
+* 0 - add
+* 1 - replace
+* 2 - do nothing (use existed value)
+* 3 - warning and add
+* 4 - warning and replace
+* 5 - warning and use existed value
+* other - error
+
 """
-function ACOV(c)
-    CovarianceType(ACOV_(c.s, 0))
+function ACOV(c; action = 0)
+    CovarianceType(ACOV_(c.s, action))
 end
 
 function RZero()

test/test.jl

@@ -826,6 +826,9 @@ end
     Metida.fit!(lmm2)
     @test Metida.m2logreml(lmm1)  ≈ Metida.m2logreml(lmm2) 
 
+    io = IOBuffer();
+
+    @test_nowarn show(io, lmm2)
 end