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FROM jupyter/datascience-notebook
USER root
RUN apt-get update && apt-get install -yq graphviz
USER $NB_USER
RUN pip install lingam graphviz

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import numpy as np


def lag(x, n=0):
    observed = np.isnan(x) == False
    observed[0] = True
    offsets = np.flatnonzero(observed)
    return offsets[np.maximum(np.cumsum(observed) - 1 - n, 0)]

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function [beta, beta0] = truncated_tls(X, y, k)
% TRUNCATED_TLS Computes the Truncated Total Least Squares solution.
%
% Inputs:
%   X : Matrix of predictors (n x p)
%   y : Target column vector (n x 1)
%   k : Truncation rank (number of singular values to KEEP)
%       Must satisfy: 1 <= k <= p
%
% Outputs: