diff --git a/src/GeoStatsFunctions.jl b/src/GeoStatsFunctions.jl
index fa34863..f600ee5 100644
--- a/src/GeoStatsFunctions.jl
+++ b/src/GeoStatsFunctions.jl
@@ -30,12 +30,22 @@ import LinearAlgebra: ⋅
 ⋅(::Missing, ::Missing) = missing
 
 include("utils.jl")
+
+# empirical models
+include("estimators.jl")
+include("algorithms.jl")
 include("empirical.jl")
+
+# theoretical models
 include("variogram.jl")
 include("covariance.jl")
 include("nesting.jl")
+
+# operations
 include("fitting.jl")
 include("sampling.jl")
+
+# plotting
 include("varioplot.jl")
 
 include("precompile.jl")
diff --git a/src/algorithms.jl b/src/algorithms.jl
new file mode 100644
index 0000000..5cd997a
--- /dev/null
+++ b/src/algorithms.jl
@@ -0,0 +1,108 @@
+# ------------------------------------------------------------------
+# Licensed under the MIT License. See LICENSE in the project root.
+# ------------------------------------------------------------------
+
+"""
+    VariogramAccumAlgo
+
+Algorithm for accumulating pairs of points in
+[`EmpiricalVariogram`](@ref) estimation.
+"""
+abstract type VariogramAccumAlgo end
+
+"""
+    accumulate(data, var₁, var₂, estim, algo)
+
+Accumulate pairs of points in `data` for variables
+`var₁` and `var₂` with variogram estimator `estim`
+and accumulation algorithm `algo`.
+"""
+function accumulate(data, var₁, var₂, estim::VariogramEstimator, algo::VariogramAccumAlgo)
+  # retrieve algorithm parameters
+  nlags = algo.nlags
+  maxlag = algo.maxlag
+  distance = algo.distance
+
+  # compute lag size
+  δh = maxlag / nlags
+
+  # table and point set
+  𝒯 = values(data)
+  𝒫 = domain(data)
+
+  # vectors for variables
+  cols = Tables.columns(𝒯)
+  z₁ = Tables.getcolumn(cols, Symbol(var₁))
+  z₂ = Tables.getcolumn(cols, Symbol(var₂))
+
+  # neighbors function
+  neighbors = neighfun(algo, 𝒫)
+
+  # skip condition
+  skip = skipfun(algo)
+
+  # early exit condition
+  exit = exitfun(algo)
+
+  # accumulation type
+  V = returntype(estim, z₁, z₂)
+
+  # lag sums and counts
+  ℒ = Meshes.lentype(𝒫)
+  Σx = zeros(ℒ, nlags)
+  Σy = zeros(V, nlags)
+  ns = zeros(Int, nlags)
+
+  # loop over points inside ball
+  @inbounds for j in 1:nelements(𝒫)
+    pⱼ = 𝒫[j]
+    z₁ⱼ = z₁[j]
+    z₂ⱼ = z₂[j]
+    for i in neighbors(j)
+      # skip to avoid double counting
+      skip(i, j) && continue
+
+      pᵢ = 𝒫[i]
+      z₁ᵢ = z₁[i]
+      z₂ᵢ = z₂[i]
+
+      # evaluate geospatial lag
+      h = evaluate(distance, pᵢ, pⱼ)
+
+      # early exit if out of range
+      exit(h) && continue
+
+      # evaluate (cross-)variance
+      v = formula(estim, z₁ᵢ, z₁ⱼ, z₂ᵢ, z₂ⱼ)
+
+      # bin (or lag) where to accumulate result
+      lag = ceil(Int, h / δh)
+      lag == 0 && @warn "duplicate coordinates found, consider using `UniqueCoords`"
+
+      if 0 < lag ≤ nlags && !ismissing(v)
+        Σx[lag] += h
+        Σy[lag] += v
+        ns[lag] += 1
+      end
+    end
+  end
+
+  # bin (or lag) size
+  lags = range(δh / 2, stop=maxlag - δh / 2, length=nlags)
+
+  # ordinate function
+  ordfun(Σy, n) = normsum(estim, Σy, n)
+
+  # variogram abscissa
+  xs = @. Σx / ns
+  xs[ns .== 0] .= lags[ns .== 0]
+
+  # variogram ordinate
+  ys = @. ordfun(Σy, ns)
+  ys[ns .== 0] .= zero(eltype(ys))
+
+  xs, ys, ns
+end
+
+include("algorithms/fullsearch.jl")
+include("algorithms/ballsearch.jl")
diff --git a/src/empirical.jl b/src/empirical.jl
index b3b1a1d..ee948da 100644
--- a/src/empirical.jl
+++ b/src/empirical.jl
@@ -2,127 +2,6 @@
 # Licensed under the MIT License. See LICENSE in the project root.
 # ------------------------------------------------------------------
 
-"""
-    VariogramEstimator
-
-A (robust) estimator of [`EmpiricalVariogram`](@ref).
-"""
-abstract type VariogramEstimator end
-
-returntype(estim::VariogramEstimator, z₁, z₂) = typeof(formula(estim, z₁[1], z₁[2], z₂[1], z₂[2]))
-
-include("estimators/matheron.jl")
-include("estimators/cressie.jl")
-
-"""
-    VariogramAccumAlgo
-
-Algorithm for accumulating pairs of points in
-[`EmpiricalVariogram`](@ref) estimation.
-"""
-abstract type VariogramAccumAlgo end
-
-"""
-    accumulate(data, var₁, var₂, estim, algo)
-
-Accumulate pairs of points in `data` for variables
-`var₁` and `var₂` with variogram estimator `estim`
-and accumulation algorithm `algo`.
-"""
-function accumulate(data, var₁, var₂, estim::VariogramEstimator, algo::VariogramAccumAlgo)
-  # retrieve algorithm parameters
-  nlags = algo.nlags
-  maxlag = algo.maxlag
-  distance = algo.distance
-
-  # compute lag size
-  δh = maxlag / nlags
-
-  # table and point set
-  𝒯 = values(data)
-  𝒫 = domain(data)
-
-  # vectors for variables
-  cols = Tables.columns(𝒯)
-  z₁ = Tables.getcolumn(cols, Symbol(var₁))
-  z₂ = Tables.getcolumn(cols, Symbol(var₂))
-
-  # neighbors function
-  neighbors = neighfun(algo, 𝒫)
-
-  # skip condition
-  skip = skipfun(algo)
-
-  # early exit condition
-  exit = exitfun(algo)
-
-  # accumulation type
-  V = returntype(estim, z₁, z₂)
-
-  # lag sums and counts
-  ℒ = Meshes.lentype(𝒫)
-  Σx = zeros(ℒ, nlags)
-  Σy = zeros(V, nlags)
-  ns = zeros(Int, nlags)
-
-  # loop over points inside ball
-  @inbounds for j in 1:nelements(𝒫)
-    pⱼ = 𝒫[j]
-    z₁ⱼ = z₁[j]
-    z₂ⱼ = z₂[j]
-    for i in neighbors(j)
-      # skip to avoid double counting
-      skip(i, j) && continue
-
-      pᵢ = 𝒫[i]
-      z₁ᵢ = z₁[i]
-      z₂ᵢ = z₂[i]
-
-      # evaluate geospatial lag
-      h = evaluate(distance, pᵢ, pⱼ)
-
-      # early exit if out of range
-      exit(h) && continue
-
-      # evaluate (cross-)variance
-      v = formula(estim, z₁ᵢ, z₁ⱼ, z₂ᵢ, z₂ⱼ)
-
-      # bin (or lag) where to accumulate result
-      lag = ceil(Int, h / δh)
-      lag == 0 && @warn "duplicate coordinates found, consider using `UniqueCoords`"
-
-      if 0 < lag ≤ nlags && !ismissing(v)
-        Σx[lag] += h
-        Σy[lag] += v
-        ns[lag] += 1
-      end
-    end
-  end
-
-  # bin (or lag) size
-  lags = range(δh / 2, stop=maxlag - δh / 2, length=nlags)
-
-  # ordinate function
-  ordfun(Σy, n) = normsum(estim, Σy, n)
-
-  # variogram abscissa
-  xs = @. Σx / ns
-  xs[ns .== 0] .= lags[ns .== 0]
-
-  # variogram ordinate
-  ys = @. ordfun(Σy, ns)
-  ys[ns .== 0] .= zero(eltype(ys))
-
-  xs, ys, ns
-end
-
-include("algorithms/fullsearch.jl")
-include("algorithms/ballsearch.jl")
-
-# ---------------------
-# EMPIRICAL VARIOGRAMS
-# ---------------------
-
 include("empirical/variogram.jl")
 include("empirical/varioplane.jl")
 include("empirical/partition.jl")
diff --git a/src/estimators.jl b/src/estimators.jl
new file mode 100644
index 0000000..f639934
--- /dev/null
+++ b/src/estimators.jl
@@ -0,0 +1,15 @@
+# ------------------------------------------------------------------
+# Licensed under the MIT License. See LICENSE in the project root.
+# ------------------------------------------------------------------
+
+"""
+    VariogramEstimator
+
+A (robust) estimator of [`EmpiricalVariogram`](@ref).
+"""
+abstract type VariogramEstimator end
+
+returntype(estim::VariogramEstimator, z₁, z₂) = typeof(formula(estim, z₁[1], z₁[2], z₂[1], z₂[2]))
+
+include("estimators/matheron.jl")
+include("estimators/cressie.jl")