.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/01_temporalTimeSeriesAnalysis/plot_autoregressiveExample.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_01_temporalTimeSeriesAnalysis_plot_autoregressiveExample.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_01_temporalTimeSeriesAnalysis_plot_autoregressiveExample.py:


Generation of a autoregressive time series
==========================================

.. GENERATED FROM PYTHON SOURCE LINES 7-9

Import requirements
-------------------

.. GENERATED FROM PYTHON SOURCE LINES 9-14

.. code-block:: Python


    import os
    import numpy as np
    import plotly.graph_objects as go








.. GENERATED FROM PYTHON SOURCE LINES 15-17

Define variables
----------------

.. GENERATED FROM PYTHON SOURCE LINES 17-22

.. code-block:: Python


    srate = 1
    T = 500
    sigma = 1.0








.. GENERATED FROM PYTHON SOURCE LINES 23-26

Create white noise
------------------


.. GENERATED FROM PYTHON SOURCE LINES 26-31

.. code-block:: Python


    time = np.arange(0, T, 1.0/srate)
    N = len(time)
    w = np.random.normal(loc=0, scale=sigma, size=N)








.. GENERATED FROM PYTHON SOURCE LINES 32-35

Create autoregressive time series
---------------------------------


.. GENERATED FROM PYTHON SOURCE LINES 35-41

.. code-block:: Python

    ar = np.empty(len(w), dtype=np.double)
    ar[0] = w[0]
    ar[1] = ar[0] + w[1]
    for i in range(2, len(w)):
        ar[i] = ar[i-1] - 0.9 * ar[i-2] + w[i]








.. GENERATED FROM PYTHON SOURCE LINES 42-45

Plot autoregressive time series
-------------------------------


.. GENERATED FROM PYTHON SOURCE LINES 45-58

.. code-block:: Python


    fig = go.Figure()
    trace = go.Scatter(x=time, y=ar, mode="lines+markers")
    fig.add_trace(trace)
    fig.update_layout(xaxis=dict(title="Time (sec)"), yaxis=dict(title="x"))

    if not os.path.exists("figures"):
        os.mkdir("figures")

    fig.write_html("figures/autoregressive.html")
    fig.write_image("figures/autoregressive.png")

    fig





.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>                        <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
            <script charset="utf-8" src="https://cdn.plot.ly/plotly-3.0.0.min.js"></script>                <div id="2d11dac9-abc1-4b52-a833-87816b198a2b" class="plotly-graph-div" style="height:100%; width:100%;"></div>            <script type="text/javascript">                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById("2d11dac9-abc1-4b52-a833-87816b198a2b")) {                    Plotly.newPlot(                        "2d11dac9-abc1-4b52-a833-87816b198a2b",                        [{"mode":"lines+markers","x":{"dtype":"f8","bdata":"AAAAAAAAAAAAAAAAAADwPwAAAAAAAABAAAAAAAAACEAAAAAAAAAQQAAAAAAAABRAAAAAAAAAGEAAAAAAAAAcQAAAAAAAACBAAAAAAAAAIkAAAAAAAAAkQAAAAAAAACZAAAAAAAAAKEAAAAAAAAAqQAAAAAAAACxAAAAAAAAALkAAAAAAAAAwQAAAAAAAADFAAAAAAAAAMkAAAAAAAAAzQAAAAAAAADRAAAAAAAAANUAAAAAAAAA2QAAAAAAAADdAAAAAAAAAOEAAAAAAAAA5QAAAAAAAADpAAAAAAAAAO0AAAAAAAAA8QAAAAAAAAD1AAAAAAAAAPkAAAAAAAAA\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\u002fQAAAAAAAEH9AAAAAAAAgf0AAAAAAADB\u002fQA=="},"y":{"dtype":"f8","bdata":"8luiz19\u002f+7\u002fkQqi2RDQOwIY3kFjPlPy\u002fXl9SOjqI+j86OggkHNoFQDdupuSdUvw\u002f7zsADolf\u002fb\u002fW2LAScjMCwJ8x+ZKIiPq\u002fxL6R6qTdyL9d5NvmS97oPzCiViJG4MS\u002fzb0nvcW1CMD1UZ8+pmoEwLozULXh1\u002fk\u002f4vLPxUVrA0CIK+SaxmvRv5YyLUsl+u6\u002fT9liyiHa5r\u002fQna5LsDP5v4TlT2enpP2\u002fiXJ6tA782L862wInARL0P5BRl5iJINe\u002fnMcVX34t+79geF9HWei1v+XY7c8XIPI\u002fBLbXdqp1\u002fD\u002fjPwYJOZzlP8hsXqEDaN6\u002feiADhFxJ5r9Ik92OWFjqvxCZS+ybeOQ\u002fgMgxp8vbBED2QZP9njwMQJbXx\u002fuaIOU\u002friaep4k1EMBCTimtkUYVwLxz5oBzE\u002fy\u002f0vBfNk8cDEDgVhlvqwwUQJ1PuBj0fwFAruBQZLts979kU11Hzi8JwM7WRevIiPq\u002f00qh4znJ9T+qPMOLh+8MQBWUDdjfsAVAlpfPiH7q1L+Axoxr42S6v6xNWdv8YdY\u002fKuRy5gpO9j+sJxKeRkXIPzE24\u002fSD1APA1AAtmHg+AMAX8W2okSbmvyj6lSHeP96\u002fedU6+Zd47j\u002f03hsXbC\u002f8P1nr5THkXPA\u002f3usXKd76879R9k42VC34v6gXX4\u002fojvG\u002f6ukaN93e7j9IFD0OPLv+P5aeMVdfhfA\u002fUMAx7AIF4D9UtCAeCkrqv30v7LjTu+2\u002fsXfVkOxN6L8pmRUOsBXlv7TCMQYT6tC\u002fzVpPLQcm7r9Wonau+HXwv7qIrJ20GOw\u002fJECZwsWv\u002fT8WCjpoxUf5P2J09zUlifu\u002fyK\u002fsDDyiF8Csuxcv4AEPwL+gHbGNMfQ\u002fi5az1BBPF0AcqByW+CMQQMbkV2k+edC\u002fwlD+XPBDFsC3tPiwq3MUwM28d+DC6es\u002f2uObQkDtEkAkTqq5OEMLQExzPvYhO+S\u002fiA\u002fsEp+WA8A\u002fmUCW6YkCwBLPXbiWtd8\u002fmrs20SGC\u002fT929H64\u002fP3yv0NDIH9GuwHA7lRSYoo\u002f5r\u002fOXM0DbiP2P5SfvdEGvwpAKKsEJJaV+T9n39l1C8n2vxynfJY5GQjATuywET6IBsA7FUqLOVHUPw4+ExyfsBBAqrCw04KMA0A4z8662GT1v8+pEarXgQPAG\u002f2g8nH58L\u002fIGxZDPnP4P8ROcFwnRfs\u002fGcmh1kBJ9T\u002fIA7wvBy\u002fxv3RhmpBfk\u002f6\u002fO+k538Gw9L+FhrE6B8XxPyEqh7pmRAhA7j4ptEaAA0BDXRwWEeHtv\u002f5VCQEn6gfAGm+hPa94AsDyRwWLv6Xkv\u002fD1Ci0FSLA\u002f3nAQHQkv4L\u002f0z+sFnxX5vwCAU+0jXUS\u002fwqnuMpRU9D\u002f45IWl3a3uP1WOLeeKhem\u002fBulg3Bl9BsAPA57SoO8KwFxpvDyt9\u002fe\u002frYw160mL5T9Wngpu9ngGQOLfQEnoQfw\u002f+jNi9H9A778AxAq3C5gBwJDnHi6cvOc\u002fmMMlFJ1tA0Au3xWrJO0CQBwED7263bW\u002fXAsqO5WVC8AuketA3xAEwEAMdMY9c+O\u002fJLIYJmYr8r8MbSQYjAf5v1yTnbmevsS\u002f6clXtFsj+T9HpElRf7v8PwbEz9Q1ot0\u002fViX2QUAW+L9c7GZjRMLqv1uaZh9L9\u002fC\u002f2Es\u002fv58l8L8BLxEbepX1P4klb+MN3A5A2RC1D8CS9T+mYTSyMDcIwAk\u002fi9UNRg3AYovDMj3Q978SIRPzgY33P0wajgjUyQtAI1SzEI6FD0CAELV0Iu2Vv67LApqSFhDAMTIlodO9EMDYDYH9p8O+P5uuOzEBzw1AMamD+it5D0DwaoB2KcqmP84uFY\u002fV1w3AyTw93RYvDcDGx1LC2i\u002fjvy5e9c91eQBAfMOmgkUGDED7e7aihqDyPzWVbFsf1gDAfTF3TNkGFMDZXcrTCRUNwNTw0FgWKgFAJiaeA2CnE0CgT3yKU4\u002f8P6DN9ZQ1bgnAfeVltD3eEcBFIKuquMHzv96JSdP2tgVA7OvXY8H2EkBkYPMSW\u002fPuPyy3aPJobhDAQP0pfoBpFMAOhvgW8u74vwySoV4TpglA1J5NRMDnEkCxznfBaZL1P1xdVeuwkhDAIrfL0dl3HsBPZMHljFYNwKXcQZvHNxdAKbwC1rVXJkDXGNaskXMVQHAwc7LtcQfAH0O0A8bAHsD0VJt0mzwVwF9VFnl3wfo\u002foDZE4vyXGkCLzqhu6okWQJTmBqgmN9Y\u002fIkTEgznzEcChFrKnBZsRwOJr6xenv+e\u002fUs1i92\u002fk8j94qM1jRaXtP5sbjiqmAeU\u002fEIB2584NwL++wdkpxdMFwKMWTwijWAPATKLMkpGurD+LUSK3fDnzP+YbDQOMovs\u002fSrsZtEIyxD8KEq32P2L+v106q3PhtQTAqD3E7vSr8b9LNzYj\u002fG70P0JhyZisBBFA4Tj2lOsOBECGht1xZwoGwDS\u002fOsFgQBLAFA38UPeE+b+QxqtvouzuPx1aptOgCAFAOGPbZ6nYB0BH0RlJa1L0P0CDDMwO+rO\u002f6wgFDamZ\u002fb\u002faa3rWhFEOwNWBB\u002fYMU\u002fu\u002fStthkl6jAkDcN99L8wEXQIxCYt8Y3BVA\u002fc4qm5cQ5D+AwslJXGcRwDTbvlfqUwTAHKYdYVv0AUAJ61btOqAUQCNbBYVfmARAaCXC4HmTAcCqBm4LhTEQwGAwdvs76wfAMgu6NlT50L\u002fuzmMiM+QLQHoB3HW2HxFAytRYJmFj5D9v\u002fn\u002fLBj4RwI5sMPBLxArAVJRYHFXY2z8qylxoJ4\u002f5P4\u002f0X7f99gtAF7bg9Bb\u002fAkA4bG9VSsPPP3oldkgoTgDAakH7LgXf5L\u002fILbNafTIDQK4\u002fFsDajw9AFhmTRh329j8Jiu\u002fXT50FwJkU+z3XjQLAkWU+nbtU2T\u002fqyUp\u002fi7MIQHDdhiM\u002f5M8\u002fvsLxh6DRC8Aigh3fELISwM3CKgIGC\u002fG\u002ftabguLpGCECO1eQDL8oLQNKtfvJpMuE\u002fYRSrVYu2AsDG98mX1Z8KwPxabEzJyf2\u002fzQeUGd5f8z9lIKs9UagUQDRDOCPh5RJA2Q0+sbsGqD+6mFCNsIQSwOnMLU0lhBLAjoLmGQUu\u002fL\u002f4es+zKuwJQLTdXFh2\u002fBZA+g+7wuBtC0DSUpUUBOj6v5rwz7QdnRHAE2f603+i8b\u002fvvny1AKADQD5whSy4NBRAqlo1D5nY7T\u002fg0eeZiQ4QwGHuHv1wQhnAQXfLCbkjCsCsZ6DI5MQHQKzUWMB+whxAWoJtmCzdF0Aay\u002fwj9l7ZP5I3GFhShhHAz5G3fg8AEcA5hF858LP1v27vTZIevRRAhQeez9GgFUD8Q5MFz7LYv7aTO+1USw7AWvEBcQtNA8Ay\u002fckxMQ4CQCud\u002fuibUQ9AiMarYS43+D+Y1w53MsQBwE0RBBl3LQ7Aa5zwnGSB\u002fb\u002fYJe5F2J0KQMhbSAcq1hZAbCKIwThS+z94CCmiUpUEwFDiTlMZrA3Al5uN0EBnAcB392JLeCf0P23XSbVKnANAYxzQKT139j9kkq\u002fbQ7Dzv6NRa83mBwfASAWeNG1Q3b866\u002feVmVgGQJW+QPUmdBFAI6RtLeLzAED\u002f0BB8Gw8BwF4grjJ0qxLAPwDN0H4\u002fCsACArJDBUn0v9AkzaZG1vg\u002fKAaZa01ADUC39n51GKkDQH3MfWcYvuq\u002f9mNHGqWO8L\u002fS8tfNpXTivw4eia\u002f7iOO\u002ft+0M9v2b6r\u002fYMXwm0MzOP6GU1JjeAPM\u002fkBhZ5Sss\u002fj\u002fWKyc1CUPWP4zZxrt1\u002fv2\u002fwrTKRfaFBsBVjdaeJMkEwCWl3rFE7uQ\u002fIq\u002fJS2MM9z\u002fRHB33klj0P8yWO\u002fC9+dA\u002fUA1cfxCbqT\u002fG3B9BB4jGP9zGBVV3QeO\u002fetoWszt38L9yyRY3qb7bv3KP3CAAld+\u002fiuTrFhbhyT+bB8tHPD30P+rveafiZQVA0Xn3oi4i9j9sa\u002fbEv8jTP8WqpAA1GQjAAjlN7+cZDMC+hlICtBrrv0t9G1z0nf4\u002fTtmfxdQmAEC49oQUe9EAQNz4ftdHBbc\u002f0jQ0D6aWBMCJd9\u002fxRoIEwCrl41URIsU\u002flbN\u002fpdAyB0AuK+\u002faGNQGQGwLtBiwgeE\u002fA3TO8MWJAcBImdMLyC\u002f\u002fv3kHHPsv8\u002fE\u002fsCBbplfPEUAGWjZcGXQQQLQK5hheLN+\u002fVIN3MZ8KFMAB7g0+Q\u002f8MwPjUj\u002fhYQNC\u002fmJy\u002f0989AkA6ASsdmpIOQLy9Yh44ogBAuvCYbjdQ+b9FYR4NKv8JwKROBJPqZQzA8FnlDwu6778lWdoaCdsLQOfykYnkpxVA7MnYEnVsEkBzMMwazu3Uv7ViJXG6hgrADd9lhSd9BMAk3A5YcxfyP11c7oMTav4\u002fxqPLQrYk6j\u002fILmIW2VbMP3gyXN2mr+K\u002fPqqWpatW8b\u002f2PrDmdzHsv8W1cBfMaQRAtB+K1HDnAEBOO3Jjf2wAQML1XU0Qze0\u002fjCCRvUoq3L9UGMY6sUb7v+AifR7HudC\u002fWS6bFkKt+z+e93fQU+8CQOzigbYyzP4\u002foPMtFDrlCsDcDkN6yP0EwPRC5bIv6s+\u002f3vGpJJcD\u002fD8OokFa6FMJQP\u002fP5rURG\u002fc\u002fdvzZh2\u002fd+79EJNT\u002fafEOwMbN2vMCzPa\u002fu6Lpa74P\u002fD+EjHl2lCP\u002fP8RULSXs2MO\u002fwvwl4ACA+L+rJPdp+drsv0DrfBAPKPO\u002f+Z1+BKd55j\u002fLJUuCQiQOQJmTRZ52nQdAy4u4zQOa3r85GMgPcj0PwFBmb\u002fTXOATAU\u002fDjdYlt+z8rF\u002fdSiyAVQE0xoP\u002f83hJAUpwlGw7Fk7\u002fY7qHCqtwLwL60BlXKvP+\u002fYgZt+bGlBkBEZfg2Qv0UQOPXIFgmMfs\u002f167gT0XaBcC6BW7hvKURwCZU0knHtAbA1ZMio67AAEC7ygXgX3kQQJJbb6e1jQlAlnLN\u002fF021D+wrVdG0wQKwKJcyAa6YxHA2PrG4zFYyT+rcAKVDucQQOJ8YXjhthVAEygAPVta9D8YOQaE+WgJwPqg6uxOvxTAA70lYKd8\u002fL\u002fFoYmvyboDQMti6JDHWwVArIFTgkrq0z+kM5FA\u002fwTZv+U+G+6y+eW\u002fr3Yzuflv9L8WugXtKUoFwKKkIFGPvAHA7XZ4cp5V3T9IVdbHef7+P7hq5f\u002feDdK\u002fwKfMmTG0AsDW1b7+Sar7vyBJlzocI9S\u002f+DJg9ZqG1j8OE9IdpB\u002fTvyh1iXIijMw\u002fcwsyGxIl67\u002fAF9RxkBGzP5zy9RQcUwJAssCuUrZ19D82yCeQPU74v1nAtLXKUwTAkJGFM39c9r8Q5ourl0rkv0\u002f2g+UKHvS\u002fAnkojvvK2L9QCBlT7kCmv9QHzfJOYwBAIAVGySlFCEA\u002f6WN9aWMAQBFBj7juF\u002fE\u002fyOsa6RXt379g9jLRpe3Lvx0Gkrf9iQRAT3odmPK1DECo11Ja+ILcPw=="},"type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermap":[{"type":"scattermap","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"}}},"xaxis":{"title":{"text":"Time (sec)"}},"yaxis":{"title":{"text":"x"}}},                        {"responsive": true}                    )                };            </script>        </div>
    </div>
    <br />
    <br />


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.119 seconds)


.. _sphx_glr_download_auto_examples_01_temporalTimeSeriesAnalysis_plot_autoregressiveExample.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_autoregressiveExample.ipynb <plot_autoregressiveExample.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_autoregressiveExample.py <plot_autoregressiveExample.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_autoregressiveExample.zip <plot_autoregressiveExample.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_