From d7d7d719eb8d5b33024bbf07a4addee4fda2d19b Mon Sep 17 00:00:00 2001 From: Debian Science Maintainers Date: Sat, 2 Mar 2019 14:59:35 +0000 Subject: [PATCH] Fix spelling Author: Rebecca N. Palmer Origin: lintian (partly) Forwarded: https://github.com/statsmodels/statsmodels/pull/5513 Gbp-Pq: Name spelling.patch --- examples/notebooks/regression_diagnostics.ipynb | 2 +- statsmodels/sandbox/nonparametric/smoothers.py | 2 +- statsmodels/sandbox/tsa/varma.py | 2 +- statsmodels/tsa/arima_model.py | 4 ++-- statsmodels/tsa/statespace/_statespace.pyx.in | 2 +- 5 files changed, 6 insertions(+), 6 deletions(-) diff --git a/examples/notebooks/regression_diagnostics.ipynb b/examples/notebooks/regression_diagnostics.ipynb index 377d78c..fae48d7 100644 --- a/examples/notebooks/regression_diagnostics.ipynb +++ b/examples/notebooks/regression_diagnostics.ipynb @@ -11,7 +11,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "This example file shows how to use a few of the ``statsmodels`` regression diagnostic tests in a real-life context. You can learn about more tests and find out more information abou the tests here on the [Regression Diagnostics page.](http://www.statsmodels.org/stable/diagnostic.html) \n", + "This example file shows how to use a few of the ``statsmodels`` regression diagnostic tests in a real-life context. You can learn about more tests and find out more information about the tests here on the [Regression Diagnostics page.](http://www.statsmodels.org/stable/diagnostic.html) \n", "\n", "Note that most of the tests described here only return a tuple of numbers, without any annotation. A full description of outputs is always included in the docstring and in the online ``statsmodels`` documentation. For presentation purposes, we use the ``zip(name,test)`` construct to pretty-print short descriptions in the examples below." ] diff --git a/statsmodels/sandbox/nonparametric/smoothers.py b/statsmodels/sandbox/nonparametric/smoothers.py index 519fbf5..308031c 100644 --- a/statsmodels/sandbox/nonparametric/smoothers.py +++ b/statsmodels/sandbox/nonparametric/smoothers.py @@ -101,7 +101,7 @@ class PolySmoother(object): """ #JP: heavily adjusted to work as plugin replacement for bspline - # smoother in gam.py initalized by function default_smoother + # smoother in gam.py initialized by function default_smoother # Only fixed exceptions, I didn't check whether it is statistically # correctand I think it is not, there are still be some dimension # problems, and there were some dimension problems initially. diff --git a/statsmodels/sandbox/tsa/varma.py b/statsmodels/sandbox/tsa/varma.py index 93ac184..c4c8d50 100644 --- a/statsmodels/sandbox/tsa/varma.py +++ b/statsmodels/sandbox/tsa/varma.py @@ -139,7 +139,7 @@ if __name__ == '__main__': C[1,1,1] = 0.5 xhat3, err3 = VARMA(x,B,C) - x = np.r_[np.zeros((P,K)),x] #prepend inital conditions + x = np.r_[np.zeros((P,K)),x] #prepend initial conditions xhat4, err4 = VARMA(x,B,C) C[1,1,1] = 1 diff --git a/statsmodels/tsa/arima_model.py b/statsmodels/tsa/arima_model.py index 6b87f97..cf4220e 100644 --- a/statsmodels/tsa/arima_model.py +++ b/statsmodels/tsa/arima_model.py @@ -902,7 +902,7 @@ class ARMA(tsbase.TimeSeriesModel): Notes ------ If fit by 'mle', it is assumed for the Kalman Filter that the initial - unkown state is zero, and that the inital variance is + unknown state is zero, and that the initial variance is P = dot(inv(identity(m**2)-kron(T,T)),dot(R,R.T).ravel('F')).reshape(r, r, order = 'F') @@ -1140,7 +1140,7 @@ class ARIMA(ARMA): Notes ------ If fit by 'mle', it is assumed for the Kalman Filter that the initial - unkown state is zero, and that the inital variance is + unknown state is zero, and that the initial variance is P = dot(inv(identity(m**2)-kron(T,T)),dot(R,R.T).ravel('F')).reshape(r, r, order = 'F') diff --git a/statsmodels/tsa/statespace/_statespace.pyx.in b/statsmodels/tsa/statespace/_statespace.pyx.in index 8579210..21d5663 100644 --- a/statsmodels/tsa/statespace/_statespace.pyx.in +++ b/statsmodels/tsa/statespace/_statespace.pyx.in @@ -344,7 +344,7 @@ cdef class {{prefix}}Statespace(object): """ initialize_known(initial_state, initial_state_cov) """ - validate_vector_shape('inital state', &initial_state.shape[0], self.k_states, None) + validate_vector_shape('initial state', &initial_state.shape[0], self.k_states, None) validate_matrix_shape('initial state covariance', &initial_state_cov.shape[0], self.k_states, self.k_states, None) self.initial_state = initial_state -- 2.30.2