diff --git a/CHANGELOG.md b/CHANGELOG.md
index 1cbc1254b0..33809b738d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -38,7 +38,8 @@
 * plot_ppc animation: improve docs and error handling (#1162)
 
 ### Deprecation
-* `credible_interval` argument replaced by `hdi_prob`throughout with exception of `plot_loo_pit` (#1176)
+* `hpd` function deprecated in favor of `hdi`. `credible_interval` argument replaced by `hdi_prob`throughout with exception of `plot_loo_pit` (#1176)
+* `plot_hpd` function deprecated in favor of `plot_hdi`. (#1190)
 
 ### Documentation
 * Add classifier to `setup.py` including Matplotlib framework (#1133)
diff --git a/arviz/plots/__init__.py b/arviz/plots/__init__.py
index 5cc2a6c087..62441edccd 100644
--- a/arviz/plots/__init__.py
+++ b/arviz/plots/__init__.py
@@ -7,7 +7,7 @@
 from .energyplot import plot_energy
 from .essplot import plot_ess
 from .forestplot import plot_forest
-from .hpdplot import plot_hpd
+from .hdiplot import plot_hdi, plot_hpd
 from .jointplot import plot_joint
 from .kdeplot import plot_kde
 from .khatplot import plot_khat
@@ -32,6 +32,7 @@
     "plot_energy",
     "plot_ess",
     "plot_forest",
+    "plot_hdi",
     "plot_hpd",
     "plot_joint",
     "plot_kde",
diff --git a/arviz/plots/backends/bokeh/__init__.py b/arviz/plots/backends/bokeh/__init__.py
index 36a01fe950..b6c0049773 100644
--- a/arviz/plots/backends/bokeh/__init__.py
+++ b/arviz/plots/backends/bokeh/__init__.py
@@ -36,7 +36,7 @@ def backend_kwarg_defaults(*args, **kwargs):
 from .energyplot import plot_energy
 from .essplot import plot_ess
 from .forestplot import plot_forest
-from .hpdplot import plot_hpd
+from .hdiplot import plot_hdi
 from .jointplot import plot_joint
 from .kdeplot import plot_kde
 from .khatplot import plot_khat
diff --git a/arviz/plots/backends/bokeh/forestplot.py b/arviz/plots/backends/bokeh/forestplot.py
index 6432514afa..91819f6018 100644
--- a/arviz/plots/backends/bokeh/forestplot.py
+++ b/arviz/plots/backends/bokeh/forestplot.py
@@ -417,7 +417,7 @@ def forestplot(self, hdi_prob, quartiles, linewidth, markersize, ax, rope):
                     x=values[mid], y=y, size=markersize * 0.75, fill_color=color,
                 )
         _title = Title()
-        _title.text = "{:.1%} hdi Interval".format(hdi_prob)
+        _title.text = "{:.1%} hdi".format(hdi_prob)
         ax.title = _title
 
         return ax
diff --git a/arviz/plots/backends/bokeh/hpdplot.py b/arviz/plots/backends/bokeh/hdiplot.py
similarity index 92%
rename from arviz/plots/backends/bokeh/hpdplot.py
rename to arviz/plots/backends/bokeh/hdiplot.py
index a5a23dc8c4..cad0ab172d 100644
--- a/arviz/plots/backends/bokeh/hpdplot.py
+++ b/arviz/plots/backends/bokeh/hdiplot.py
@@ -1,4 +1,4 @@
-"""Bokeh hpdplot."""
+"""Bokeh hdiplot."""
 from itertools import cycle
 
 import bokeh.plotting as bkp
@@ -9,8 +9,8 @@
 from .. import show_layout
 
 
-def plot_hpd(ax, x_data, y_data, plot_kwargs, fill_kwargs, backend_kwargs, show):
-    """Bokeh hpd plot."""
+def plot_hdi(ax, x_data, y_data, plot_kwargs, fill_kwargs, backend_kwargs, show):
+    """Bokeh hdi plot."""
     if backend_kwargs is None:
         backend_kwargs = {}
 
diff --git a/arviz/plots/backends/bokeh/loopitplot.py b/arviz/plots/backends/bokeh/loopitplot.py
index 78c9628561..11a00c8c3e 100644
--- a/arviz/plots/backends/bokeh/loopitplot.py
+++ b/arviz/plots/backends/bokeh/loopitplot.py
@@ -4,7 +4,7 @@
 
 from . import backend_kwarg_defaults
 from .. import show_layout
-from ...hpdplot import plot_hpd
+from ...hdiplot import plot_hdi
 from ...kdeplot import _fast_kde
 
 
@@ -19,10 +19,10 @@ def plot_loo_pit(
     p025,
     fill_kwargs,
     ecdf_fill,
-    use_hpd,
+    use_hdi,
     x_vals,
     unif_densities,
-    hpd_kwargs,
+    hdi_kwargs,
     n_unif,
     unif,
     plot_unif_kwargs,
@@ -114,15 +114,15 @@ def plot_loo_pit(
                     line_width=plot_unif_kwargs.get("linewidth", 1.0),
                 )
     else:
-        if use_hpd:
-            plot_hpd(
+        if use_hdi:
+            plot_hdi(
                 x_vals,
                 unif_densities,
                 backend="bokeh",
                 ax=ax,
                 backend_kwargs={},
                 show=False,
-                **hpd_kwargs
+                **hdi_kwargs
             )
         else:
             for idx in range(n_unif):
diff --git a/arviz/plots/backends/bokeh/posteriorplot.py b/arviz/plots/backends/bokeh/posteriorplot.py
index 17eb494bbb..c48d3a8c20 100644
--- a/arviz/plots/backends/bokeh/posteriorplot.py
+++ b/arviz/plots/backends/bokeh/posteriorplot.py
@@ -195,24 +195,24 @@ def display_point_estimate(max_data):
 
         ax.text(x=[point_value], y=[max_data * 0.8], text=[point_text], text_align="center")
 
-    def display_hpd(max_data):
+    def display_hdi(max_data):
         # np.ndarray with 2 entries, min and max
         # pylint: disable=line-too-long
         hdi_probs = hdi(values, hdi_prob=hdi_prob, multimodal=multimodal)  # type: np.ndarray
 
-        for hpdi in np.atleast_2d(hdi_probs):
+        for hdi_i in np.atleast_2d(hdi_probs):
             ax.line(
-                hpdi,
+                hdi_i,
                 (max_data * 0.02, max_data * 0.02),
                 line_width=linewidth * 2,
                 line_color="black",
             )
 
             ax.text(
-                x=list(hpdi) + [(hpdi[0] + hpdi[1]) / 2],
+                x=list(hdi_i) + [(hdi_i[0] + hdi_i[1]) / 2],
                 y=[max_data * 0.07, max_data * 0.07, max_data * 0.3],
-                text=list(map(str, map(lambda x: round_num(x, round_to), hpdi)))
-                + [format_as_percent(hdi_prob) + " HPD"],
+                text=list(map(str, map(lambda x: round_num(x, round_to), hdi_i)))
+                + [format_as_percent(hdi_prob) + " HDI"],
                 text_align="center",
             )
 
@@ -254,7 +254,7 @@ def format_axes():
     format_axes()
     max_data = hist.max()
     if hdi_prob != "hide":
-        display_hpd(max_data)
+        display_hdi(max_data)
     display_point_estimate(max_data)
     display_ref_val(max_data)
     display_rope(max_data)
diff --git a/arviz/plots/backends/matplotlib/__init__.py b/arviz/plots/backends/matplotlib/__init__.py
index c28c4f3023..8c3026c334 100644
--- a/arviz/plots/backends/matplotlib/__init__.py
+++ b/arviz/plots/backends/matplotlib/__init__.py
@@ -31,7 +31,7 @@ def backend_show(show):
 from .energyplot import plot_energy
 from .essplot import plot_ess
 from .forestplot import plot_forest
-from .hpdplot import plot_hpd
+from .hdiplot import plot_hdi
 from .jointplot import plot_joint
 from .kdeplot import plot_kde
 from .khatplot import plot_khat
diff --git a/arviz/plots/backends/matplotlib/densityplot.py b/arviz/plots/backends/matplotlib/densityplot.py
index 8f279d423a..acb4053cb6 100644
--- a/arviz/plots/backends/matplotlib/densityplot.py
+++ b/arviz/plots/backends/matplotlib/densityplot.py
@@ -122,7 +122,7 @@ def _d_helper(
     markersize : float
         Size of markers
     hdi_prob : float
-        hdi intervals. Defaults to 0.94
+        Probability for the highest density interval. Defaults to 0.94
     point_estimate : Optional[str]
         Plot point estimate per variable. Values should be 'mean', 'median', 'mode' or None.
         Defaults to 'auto' i.e. it falls back to default set in rcParams.
diff --git a/arviz/plots/backends/matplotlib/forestplot.py b/arviz/plots/backends/matplotlib/forestplot.py
index 1ba5519143..d16786497a 100644
--- a/arviz/plots/backends/matplotlib/forestplot.py
+++ b/arviz/plots/backends/matplotlib/forestplot.py
@@ -338,7 +338,7 @@ def forestplot(
                     color=color,
                 )
         ax.tick_params(labelsize=xt_labelsize)
-        ax.set_title("{:.1%} hdi Interval".format(hdi_prob), fontsize=titlesize, wrap=True)
+        ax.set_title("{:.1%} hdi".format(hdi_prob), fontsize=titlesize, wrap=True)
         if rope is None or isinstance(rope, dict):
             return
         elif len(rope) == 2:
diff --git a/arviz/plots/backends/matplotlib/hpdplot.py b/arviz/plots/backends/matplotlib/hdiplot.py
similarity index 79%
rename from arviz/plots/backends/matplotlib/hpdplot.py
rename to arviz/plots/backends/matplotlib/hdiplot.py
index 2293407708..db786ee4a2 100644
--- a/arviz/plots/backends/matplotlib/hpdplot.py
+++ b/arviz/plots/backends/matplotlib/hdiplot.py
@@ -1,16 +1,16 @@
-"""Matplotlib hpdplot."""
+"""Matplotlib hdiplot."""
 import warnings
 import matplotlib.pyplot as plt
 
 from . import backend_show
 
 
-def plot_hpd(ax, x_data, y_data, plot_kwargs, fill_kwargs, backend_kwargs, show):
-    """Matplotlib hpd plot."""
+def plot_hdi(ax, x_data, y_data, plot_kwargs, fill_kwargs, backend_kwargs, show):
+    """Matplotlib hdi plot."""
     if backend_kwargs is not None:
         warnings.warn(
             (
-                "Argument backend_kwargs has not effect in matplotlib.plot_hpd"
+                "Argument backend_kwargs has not effect in matplotlib.plot_hdi"
                 "Supplied value won't be used"
             )
         )
diff --git a/arviz/plots/backends/matplotlib/loopitplot.py b/arviz/plots/backends/matplotlib/loopitplot.py
index f50fc908e8..d21070fe37 100644
--- a/arviz/plots/backends/matplotlib/loopitplot.py
+++ b/arviz/plots/backends/matplotlib/loopitplot.py
@@ -4,7 +4,7 @@
 
 from . import backend_kwarg_defaults, backend_show
 from ....numeric_utils import _fast_kde
-from ...hpdplot import plot_hpd
+from ...hdiplot import plot_hdi
 
 
 def plot_loo_pit(
@@ -18,10 +18,10 @@ def plot_loo_pit(
     p025,
     fill_kwargs,
     ecdf_fill,
-    use_hpd,
+    use_hdi,
     x_vals,
     unif_densities,
-    hpd_kwargs,
+    hdi_kwargs,
     n_unif,
     unif,
     plot_unif_kwargs,
@@ -54,8 +54,8 @@ def plot_loo_pit(
         else:
             ax.plot(unif_ecdf, p975 - unif_ecdf, unif_ecdf, p025 - unif_ecdf, **plot_unif_kwargs)
     else:
-        if use_hpd:
-            plot_hpd(x_vals, unif_densities, **hpd_kwargs)
+        if use_hdi:
+            plot_hdi(x_vals, unif_densities, **hdi_kwargs)
         else:
             for idx in range(n_unif):
                 unif_density, _, _ = _fast_kde(unif[idx, :], xmin=0, xmax=1)
@@ -64,7 +64,7 @@ def plot_loo_pit(
 
     ax.tick_params(labelsize=xt_labelsize)
     if legend:
-        if not (use_hpd or (ecdf and ecdf_fill)):
+        if not (use_hdi or (ecdf and ecdf_fill)):
             label = "{:.3g}% credible interval".format(credible_interval) if ecdf else "Uniform"
             ax.plot([], label=label, **plot_unif_kwargs)
         ax.legend()
diff --git a/arviz/plots/backends/matplotlib/posteriorplot.py b/arviz/plots/backends/matplotlib/posteriorplot.py
index b8e21aa9d3..fa9ff17fec 100644
--- a/arviz/plots/backends/matplotlib/posteriorplot.py
+++ b/arviz/plots/backends/matplotlib/posteriorplot.py
@@ -195,37 +195,37 @@ def display_point_estimate():
             horizontalalignment="center",
         )
 
-    def display_hpd():
+    def display_hdi():
         # np.ndarray with 2 entries, min and max
         # pylint: disable=line-too-long
         hdi_probs = hdi(values, hdi_prob=hdi_prob, multimodal=multimodal)  # type: np.ndarray
 
-        for hpdi in np.atleast_2d(hdi_probs):
+        for hdi_i in np.atleast_2d(hdi_probs):
             ax.plot(
-                hpdi,
+                hdi_i,
                 (plot_height * 0.02, plot_height * 0.02),
                 lw=linewidth * 2,
                 color="k",
                 solid_capstyle="butt",
             )
             ax.text(
-                hpdi[0],
+                hdi_i[0],
                 plot_height * 0.07,
-                round_num(hpdi[0], round_to),
+                round_num(hdi_i[0], round_to),
                 size=ax_labelsize,
                 horizontalalignment="center",
             )
             ax.text(
-                hpdi[1],
+                hdi_i[1],
                 plot_height * 0.07,
-                round_num(hpdi[1], round_to),
+                round_num(hdi_i[1], round_to),
                 size=ax_labelsize,
                 horizontalalignment="center",
             )
             ax.text(
-                (hpdi[0] + hpdi[1]) / 2,
+                (hdi_i[0] + hdi_i[1]) / 2,
                 plot_height * 0.3,
-                format_as_percent(hdi_prob) + " HPD",
+                format_as_percent(hdi_prob) + " HDI",
                 size=ax_labelsize,
                 horizontalalignment="center",
             )
@@ -270,7 +270,7 @@ def format_axes():
 
     format_axes()
     if hdi_prob != "hide":
-        display_hpd()
+        display_hdi()
     display_point_estimate()
     display_ref_val()
     display_rope()
diff --git a/arviz/plots/densityplot.py b/arviz/plots/densityplot.py
index 10bce051e6..9e31de1a34 100644
--- a/arviz/plots/densityplot.py
+++ b/arviz/plots/densityplot.py
@@ -40,8 +40,8 @@ def plot_density(
 ):
     """Generate KDE plots for continuous variables and histograms for discrete ones.
 
-    Plots are truncated at their 100*(1-alpha)% hpd intervals. Plots are grouped per variable
-    and colors assigned to models.
+    Plots are truncated at their 100*(1-alpha)% highest density intervals. Plots are grouped per
+    variable and colors assigned to models.
 
     Parameters
     ----------
@@ -63,7 +63,8 @@ def plot_density(
     transform : callable
         Function to transform data (defaults to None i.e. the identity function)
     hdi_prob : float
-        hpd interval. Should be in the interval (0, 1]. Defaults to 0.94.
+        Probability for the highest density interval. Should be in the interval (0, 1].
+        Defaults to 0.94.
     point_estimate : Optional[str]
         Plot point estimate per variable. Values should be 'mean', 'median', 'mode' or None.
         Defaults to 'auto' i.e. it falls back to default set in rcParams.
@@ -75,8 +76,8 @@ def plot_density(
     outline : bool
         Use a line to draw KDEs and histograms. Default to True
     hdi_markers : str
-        A valid `matplotlib.markers` like 'v', used to indicate the limits of the hpd interval.
-        Defaults to empty string (no marker).
+        A valid `matplotlib.markers` like 'v', used to indicate the limits of the highest density
+        interval. Defaults to empty string (no marker).
     shade : Optional[float]
         Alpha blending value for the shaded area under the curve, between 0 (no shade) and 1
         (opaque). Defaults to 0.
@@ -132,7 +133,7 @@ def plot_density(
 
         >>> az.plot_density([centered, non_centered], var_names=["mu"], group="prior")
 
-    Specify hpd interval
+    Specify highest density interval
 
     .. plot::
         :context: close-figs
diff --git a/arviz/plots/hpdplot.py b/arviz/plots/hdiplot.py
similarity index 82%
rename from arviz/plots/hpdplot.py
rename to arviz/plots/hdiplot.py
index b6ac0f6f67..ba5be26b8c 100644
--- a/arviz/plots/hpdplot.py
+++ b/arviz/plots/hdiplot.py
@@ -1,4 +1,6 @@
-"""Plot hpd intervals for regression data."""
+"""Plot highest density intervals for regression data."""
+import warnings
+
 import numpy as np
 from scipy.interpolate import griddata
 from scipy.signal import savgol_filter
@@ -9,7 +11,7 @@
 from ..utils import credible_interval_warning
 
 
-def plot_hpd(
+def plot_hdi(
     x,
     y,
     hdi_prob=None,
@@ -33,13 +35,13 @@ def plot_hpd(
     x : array-like
         Values to plot
     y : array-like
-        values from which to compute the hpd. Assumed shape (chain, draw, \*shape).
+        values from which to compute the hdi. Assumed shape (chain, draw, \*shape).
     hdi_prob : float, optional
-        HDI interval to plot. Defaults to 0.94.
+        Probability for the highest density interval. Defaults to 0.94.
     color : str
-        Color used for the limits of the HPD interval and fill. Should be a valid matplotlib color
+        Color used for the limits of the hdi and fill. Should be a valid matplotlib color
     circular : bool, optional
-        Whether to compute the hpd taking into account `x` is a circular variable
+        Whether to compute the hdi taking into account `x` is a circular variable
         (in the range [-np.pi, np.pi]) or not. Defaults to False (i.e non-circular variables).
     smooth : boolean
         If True the result will be smoothed by first computing a linear interpolation of the data
@@ -51,7 +53,7 @@ def plot_hpd(
     fill_kwargs : dict
         Keywords passed to `fill_between` (use fill_kwargs={'alpha': 0} to disable fill).
     plot_kwargs : dict
-        Keywords passed to HPD limits
+        Keywords passed to hdi limits
     ax: axes, optional
         Matplotlib axes or bokeh figures.
     backend: str, optional
@@ -109,14 +111,14 @@ def plot_hpd(
         smooth_kwargs.setdefault("polyorder", 2)
         x_data = np.linspace(x.min(), x.max(), 200)
         x_data[0] = (x_data[0] + x_data[1]) / 2
-        hpd_interp = griddata(x, hdi_, x_data)
-        y_data = savgol_filter(hpd_interp, axis=0, **smooth_kwargs)
+        hdi_interp = griddata(x, hdi_, x_data)
+        y_data = savgol_filter(hdi_interp, axis=0, **smooth_kwargs)
     else:
         idx = np.argsort(x)
         x_data = x[idx]
         y_data = hdi_[idx]
 
-    hpdplot_kwargs = dict(
+    hdiplot_kwargs = dict(
         ax=ax,
         x_data=x_data,
         y_data=y_data,
@@ -131,6 +133,11 @@ def plot_hpd(
     backend = backend.lower()
 
     # TODO: Add backend kwargs
-    plot = get_plotting_function("plot_hpd", "hpdplot", backend)
-    ax = plot(**hpdplot_kwargs)
+    plot = get_plotting_function("plot_hdi", "hdiplot", backend)
+    ax = plot(**hdiplot_kwargs)
     return ax
+
+
+def plot_hpd(*args, **kwargs):  # noqa: D103
+    warnings.warn("plot_hdi has been deprecated, please use plot_hdi", DeprecationWarning)
+    return plot_hdi(*args, **kwargs)
diff --git a/arviz/plots/loopitplot.py b/arviz/plots/loopitplot.py
index 4a1cf9e72e..e4cff48f6d 100644
--- a/arviz/plots/loopitplot.py
+++ b/arviz/plots/loopitplot.py
@@ -22,7 +22,7 @@ def plot_loo_pit(
     ecdf=False,
     ecdf_fill=True,
     n_unif=100,
-    use_hpd=False,
+    use_hdi=False,
     credible_interval=None,
     figsize=None,
     textsize=None,
@@ -31,7 +31,7 @@ def plot_loo_pit(
     ax=None,
     plot_kwargs=None,
     plot_unif_kwargs=None,
-    hpd_kwargs=None,
+    hdi_kwargs=None,
     fill_kwargs=None,
     backend=None,
     backend_kwargs=None,
@@ -64,10 +64,10 @@ def plot_loo_pit(
         border lines.
     n_unif : int, optional
         Number of datasets to simulate and overlay from the uniform distribution.
-    use_hpd : bool, optional
-        Use plot_hpd to fill between hpd values instead of overlaying the uniform distributions.
+    use_hdi : bool, optional
+        Use plot_hdi to fill between hdi values instead of overlaying the uniform distributions.
     credible_interval : float, optional
-        Credible interval of the hpd or of the ECDF theoretical credible interval
+        Credible interval of the hdi or of the ECDF theoretical credible interval
     figsize : figure size tuple, optional
         If None, size is (8 + numvars, 8 + numvars)
     textsize: int, optional
@@ -85,8 +85,8 @@ def plot_loo_pit(
     plot_unif_kwargs : dict, optional
         Additional keywords passed to ax.plot for overlaid uniform distributions or
         for beta credible interval lines if ``ecdf=True``
-    hpd_kwargs : dict, optional
-        Additional keywords passed to az.plot_hpd
+    hdi_kwargs : dict, optional
+        Additional keywords passed to az.plot_hdi
     fill_kwargs : dict, optional
         Additional kwargs passed to ax.fill_between
     backend: str, optional
@@ -119,7 +119,7 @@ def plot_loo_pit(
         >>> idata = az.load_arviz_data("centered_eight")
         >>> az.plot_loo_pit(idata=idata, y="obs")
 
-    Fill the area containing the 94% credible interval of the difference between uniform
+    Fill the area containing the 94% highest density interval of the difference between uniform
     variables empirical CDF and the real uniform CDF. A LOO-PIT ECDF clearly outside of these
     theoretical boundaries indicates that the observations and the posterior predictive
     samples do not follow the same distribution.
@@ -130,8 +130,8 @@ def plot_loo_pit(
         >>> az.plot_loo_pit(idata=idata, y="obs", ecdf=True)
 
     """
-    if ecdf and use_hpd:
-        raise ValueError("use_hpd is incompatible with ecdf plot")
+    if ecdf and use_hdi:
+        raise ValueError("use_hdi is incompatible with ecdf plot")
 
     (figsize, _, _, xt_labelsize, linewidth, _) = _scale_fig_size(figsize, textsize, 1, 1)
 
@@ -210,14 +210,14 @@ def plot_loo_pit(
 
         unif = np.random.uniform(size=(n_unif, loo_pit.size))
         x_vals = np.linspace(0, 1, len(loo_pit_kde))
-        if use_hpd:
-            if hpd_kwargs is None:
-                hpd_kwargs = {}
-            hpd_kwargs.setdefault("color", to_hex(hsv_to_rgb(light_color)))
-            hpd_fill_kwargs = hpd_kwargs.pop("fill_kwargs", {})
-            hpd_fill_kwargs.setdefault("label", "Uniform HPD")
-            hpd_kwargs["fill_kwargs"] = hpd_fill_kwargs
-            hpd_kwargs["credible_interval"] = credible_interval
+        if use_hdi:
+            if hdi_kwargs is None:
+                hdi_kwargs = {}
+            hdi_kwargs.setdefault("color", to_hex(hsv_to_rgb(light_color)))
+            hdi_fill_kwargs = hdi_kwargs.pop("fill_kwargs", {})
+            hdi_fill_kwargs.setdefault("label", "Uniform hdi")
+            hdi_kwargs["fill_kwargs"] = hdi_fill_kwargs
+            hdi_kwargs["credible_interval"] = credible_interval
 
             unif_densities = np.empty((n_unif, len(loo_pit_kde)))
 
@@ -232,10 +232,10 @@ def plot_loo_pit(
         p025=p025,
         fill_kwargs=fill_kwargs,
         ecdf_fill=ecdf_fill,
-        use_hpd=use_hpd,
+        use_hdi=use_hdi,
         x_vals=x_vals,
         unif_densities=unif_densities,
-        hpd_kwargs=hpd_kwargs,
+        hdi_kwargs=hdi_kwargs,
         n_unif=n_unif,
         unif=unif,
         plot_unif_kwargs=plot_unif_kwargs,
@@ -255,12 +255,12 @@ def plot_loo_pit(
     if backend == "bokeh":
 
         if (
-            loo_pit_kwargs["hpd_kwargs"] is not None
-            and "fill_kwargs" in loo_pit_kwargs["hpd_kwargs"]
-            and loo_pit_kwargs["hpd_kwargs"]["fill_kwargs"] is not None
-            and "label" in loo_pit_kwargs["hpd_kwargs"]["fill_kwargs"]
+            loo_pit_kwargs["hdi_kwargs"] is not None
+            and "fill_kwargs" in loo_pit_kwargs["hdi_kwargs"]
+            and loo_pit_kwargs["hdi_kwargs"]["fill_kwargs"] is not None
+            and "label" in loo_pit_kwargs["hdi_kwargs"]["fill_kwargs"]
         ):
-            loo_pit_kwargs["hpd_kwargs"]["fill_kwargs"].pop("label")
+            loo_pit_kwargs["hdi_kwargs"]["fill_kwargs"].pop("label")
         loo_pit_kwargs.pop("legend")
         loo_pit_kwargs.pop("xt_labelsize")
         loo_pit_kwargs.pop("credible_interval")
diff --git a/arviz/plots/posteriorplot.py b/arviz/plots/posteriorplot.py
index 6c6b0c4c98..7245df0740 100644
--- a/arviz/plots/posteriorplot.py
+++ b/arviz/plots/posteriorplot.py
@@ -64,8 +64,8 @@ def plot_posterior(
         Text size scaling factor for labels, titles and lines. If None it will be autoscaled based
         on figsize.
     hdi_prob: float, optional
-        Plots highest posterior density interval for chosen percentage of density.
-        Use 'hide' to hide the HPD interval. Defaults to 0.94.
+        Plots highest density interval for chosen percentage of density.
+        Use 'hide' to hide the highest density interval. Defaults to 0.94.
     multimodal: bool
         If true (default) it may compute more than one credible interval if the distribution is
         multimodal and the modes are well separated.
@@ -184,7 +184,7 @@ def plot_posterior(
 
         >>> az.plot_posterior(data, var_names=['mu'], kind='hist')
 
-    Change size of HPD interval
+    Change size of highest density interval
 
     .. plot::
         :context: close-figs
diff --git a/arviz/plots/violinplot.py b/arviz/plots/violinplot.py
index 0daad2087c..39ea40231d 100644
--- a/arviz/plots/violinplot.py
+++ b/arviz/plots/violinplot.py
@@ -72,8 +72,8 @@ def plot_violin(
     figsize: tuple
         Figure size. If None it will be defined automatically.
     textsize: int
-        Text size of the point_estimates, axis ticks, and HPD. If None it will be autoscaled
-        based on figsize.
+        Text size of the point_estimates, axis ticks, and highest density interval. If None it will
+        be autoscaled based on figsize.
     sharex: bool
         Defaults to True, violinplots share a common x-axis scale.
     sharey: bool
diff --git a/arviz/stats/stats.py b/arviz/stats/stats.py
index e87031e00c..a6c112d47f 100644
--- a/arviz/stats/stats.py
+++ b/arviz/stats/stats.py
@@ -387,7 +387,7 @@ def hdi(
     skipna: bool
         If true ignores nan values when computing the hdi interval. Defaults to false.
     group: str, optional
-        Specifies which InferenceData group should be used to calculate hpd.
+        Specifies which InferenceData group should be used to calculate hdi.
         Defaults to 'posterior'
     var_names: list, optional
         Names of variables to include in the hdi report. Prefix the variables by `~`
diff --git a/arviz/tests/base_tests/test_plots_bokeh.py b/arviz/tests/base_tests/test_plots_bokeh.py
index 3c4d8799de..cb98bf67d1 100644
--- a/arviz/tests/base_tests/test_plots_bokeh.py
+++ b/arviz/tests/base_tests/test_plots_bokeh.py
@@ -25,7 +25,7 @@
     plot_energy,
     plot_ess,
     plot_forest,
-    plot_hpd,
+    plot_hdi,
     plot_joint,
     plot_kde,
     plot_khat,
@@ -488,8 +488,8 @@ def test_plot_forest_bad(models, model_fits):
         {"smooth": False},
     ],
 )
-def test_plot_hpd(models, data, kwargs):
-    axis = plot_hpd(
+def test_plot_hdi(models, data, kwargs):
+    axis = plot_hdi(
         data["y"], models.model_1.posterior["theta"], backend="bokeh", show=False, **kwargs
     )
     assert axis
@@ -602,9 +602,9 @@ def test_plot_khat_bad_input(models):
     [
         {},
         {"n_unif": 50},
-        {"use_hpd": True, "color": "gray"},
-        {"use_hpd": True, "credible_interval": 0.68, "plot_kwargs": {"alpha": 0.9}},
-        {"use_hpd": True, "hpd_kwargs": {"smooth": False}},
+        {"use_hdi": True, "color": "gray"},
+        {"use_hdi": True, "credible_interval": 0.68, "plot_kwargs": {"alpha": 0.9}},
+        {"use_hdi": True, "hdi_kwargs": {"smooth": False}},
         {"ecdf": True},
         {"ecdf": True, "ecdf_fill": False, "plot_unif_kwargs": {"line_dash": "--"}},
         {"ecdf": True, "credible_interval": 0.97, "fill_kwargs": {"color": "red"}},
@@ -616,10 +616,10 @@ def test_plot_loo_pit(models, kwargs):
 
 
 def test_plot_loo_pit_incompatible_args(models):
-    """Test error when both ecdf and use_hpd are True."""
+    """Test error when both ecdf and use_hdi are True."""
     with pytest.raises(ValueError, match="incompatible"):
         plot_loo_pit(
-            idata=models.model_1, y="y", ecdf=True, use_hpd=True, backend="bokeh", show=False
+            idata=models.model_1, y="y", ecdf=True, use_hdi=True, backend="bokeh", show=False
         )
 
 
diff --git a/arviz/tests/base_tests/test_plots_matplotlib.py b/arviz/tests/base_tests/test_plots_matplotlib.py
index eebba74586..a01a62465a 100644
--- a/arviz/tests/base_tests/test_plots_matplotlib.py
+++ b/arviz/tests/base_tests/test_plots_matplotlib.py
@@ -34,7 +34,7 @@
     plot_compare,
     plot_kde,
     plot_khat,
-    plot_hpd,
+    plot_hdi,
     plot_dist,
     plot_rank,
     plot_elpd,
@@ -805,8 +805,8 @@ def test_plot_compare_no_ic(models):
         {"smooth": False},
     ],
 )
-def test_plot_hpd(models, data, kwargs):
-    plot_hpd(data["y"], models.model_1.posterior["theta"], **kwargs)
+def test_plot_hdi(models, data, kwargs):
+    plot_hdi(data["y"], models.model_1.posterior["theta"], **kwargs)
 
 
 @pytest.mark.parametrize("limits", [(-10.0, 10.0), (-5, 5), (None, None)])
@@ -1076,9 +1076,9 @@ def test_plot_ess_no_divergences(models):
     [
         {},
         {"n_unif": 50, "legend": False},
-        {"use_hpd": True, "color": "gray"},
-        {"use_hpd": True, "credible_interval": 0.68, "plot_kwargs": {"ls": "--"}},
-        {"use_hpd": True, "hpd_kwargs": {"smooth": False}},
+        {"use_hdi": True, "color": "gray"},
+        {"use_hdi": True, "credible_interval": 0.68, "plot_kwargs": {"ls": "--"}},
+        {"use_hdi": True, "hdi_kwargs": {"smooth": False}},
         {"ecdf": True},
         {"ecdf": True, "ecdf_fill": False, "plot_unif_kwargs": {"ls": "--"}},
         {"ecdf": True, "credible_interval": 0.97, "fill_kwargs": {"hatch": "/"}},
@@ -1090,9 +1090,9 @@ def test_plot_loo_pit(models, kwargs):
 
 
 def test_plot_loo_pit_incompatible_args(models):
-    """Test error when both ecdf and use_hpd are True."""
+    """Test error when both ecdf and use_hdi are True."""
     with pytest.raises(ValueError, match="incompatible"):
-        plot_loo_pit(idata=models.model_1, y="y", ecdf=True, use_hpd=True)
+        plot_loo_pit(idata=models.model_1, y="y", ecdf=True, use_hdi=True)
 
 
 @pytest.mark.parametrize(
diff --git a/doc/api.rst b/doc/api.rst
index 35dffd86d3..d21abb9fdb 100644
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -21,7 +21,7 @@ Plots
     plot_energy
     plot_ess
     plot_forest
-    plot_hpd
+    plot_hdi
     plot_joint
     plot_kde
     plot_khat
@@ -45,7 +45,7 @@ Stats
 
     apply_test_function
     compare
-    hpd
+    hdi
     loo
     loo_pit
     psislw
diff --git a/examples/bokeh/bokeh_plot_hpd.py b/examples/bokeh/bokeh_plot_hdi.py
similarity index 84%
rename from examples/bokeh/bokeh_plot_hpd.py
rename to examples/bokeh/bokeh_plot_hdi.py
index f1a0a54ab2..f6d222475e 100644
--- a/examples/bokeh/bokeh_plot_hpd.py
+++ b/examples/bokeh/bokeh_plot_hdi.py
@@ -1,5 +1,5 @@
 """
-Plot HPD
+Plot HDI
 ========
 
 _thumb: .8, .8
@@ -13,7 +13,7 @@
 y_data_rep = np.random.normal(y_data, 0.5, (200, 100))
 x_data_sorted = np.sort(x_data)
 
-ax = az.plot_hpd(x_data, y_data_rep, color="red", backend="bokeh", show=False)
+ax = az.plot_hdi(x_data, y_data_rep, color="red", backend="bokeh", show=False)
 ax.line(x_data_sorted, 2 + x_data_sorted * 0.5, line_color="black", line_width=3)
 
 if az.rcParams["plot.bokeh.show"]:
diff --git a/examples/matplotlib/mpl_plot_hpd.py b/examples/matplotlib/mpl_plot_hdi.py
similarity index 80%
rename from examples/matplotlib/mpl_plot_hpd.py
rename to examples/matplotlib/mpl_plot_hdi.py
index 5b4df904a3..249ba363cf 100644
--- a/examples/matplotlib/mpl_plot_hpd.py
+++ b/examples/matplotlib/mpl_plot_hdi.py
@@ -1,5 +1,5 @@
 """
-Plot HPD
+Plot HDI
 ========
 
 _thumb: .8, .8
@@ -14,6 +14,6 @@
 y_data = 2 + x_data * 0.5
 y_data_rep = np.random.normal(y_data, 0.5, (200, 100))
 plt.plot(x_data, y_data, "C6")
-az.plot_hpd(x_data, y_data_rep, color="k", plot_kwargs={"ls": "--"})
+az.plot_hdi(x_data, y_data_rep, color="k", plot_kwargs={"ls": "--"})
 
 plt.show()