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    Dear Elena,<br>
    <br>
    thank you for your question and for showing a subset of your data. <br>
    <br>
    ad 2: It might be that you have rethink how you are breaking down
    sexual reproduction in your system into separate steps. How are your
    'number of flowers' and 'number of fruits' variables related? Does
    every fruit result in a new, established plant by the end of the
    time step? If so, then I can imagine that your population is
    exploding in size.<br>
    <br>
    On the other hand, if the number of fruits per flower is a constant,
    it should be added with the 'fecConstants' argument in 'makeFecObj'.
    Also the per-seed-seedling-establishment-rate can be added in
    'fecConstants'. Good that you studied the second chapter of the
    appendix to Merow et al. 2014, which contains an example with
    IPMpack-code that seems relevant for your species as well:
    <a class="moz-txt-link-freetext" href="http://tinyurl.com/ndkh99r">http://tinyurl.com/ndkh99r</a><br>
    <br>
    Perhaps it is a good idea to discuss your species' life cycle with
    your advisors.<br>
    <br>
    best wishes,<br>
    Eelke<br>
    <br>
    PS: ad 1: It might be that you have rather few deaths in your
    dataset, making it hard for binomial regression models to fit all
    parameters. However, it might also be that you are having
    difficulties with reading your data into R, unrelated to IPMpack.<br>
    <br>
    <br>
    <div class="moz-cite-prefix">On 09/02/15 18:04, Elena S. wrote:<br>
    </div>
    <blockquote cite="mid:DUB127-W667C64DDD3E0138913306AA0270@phx.gbl"
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      <div dir="ltr">Hi everybody,<br>
        <br>
        <span id="result_box" lang="en"><span>Congratulation for the
            pack, is very useful. <br>
          </span></span>I'm a PhD student that use I<span
          id="result_box" lang="en"><span class="hps">PMpack</span> <span
            class="hps">to analyze</span> <span class="hps">different
            populations</span> <span class="hps">of</span> a <span
            class="hps">perennial plant species</span><span> (so I have
            3 years of data for every population). <br>
          </span> <br>
          <span class="hps">I have two questions</span><span>:</span><br>
          <span class="hps">1)</span> <span class="hps">in one of the</span>
          <span class="hps">populations</span> I <span class="hps">have</span>
          many <span class="hps">NA</span><span>,</span> <span
            class="hps">both in</span> <span class="hps">size</span> <span
            class="hps">and in</span> <span class="hps">sizeNext</span><span>
            columns, consequently</span> <span class="hps">also</span>
          <span class="hps">in</span> <span class="hps">fec0</span> <span
            class="hps atn">(</span><span>probability of</span> <span
            class="hps">flowering)</span> <span class="hps">and</span>
          <span class="hps">fec1</span> <span class="hps atn">(</span><span>number
            of fruit</span><span>)</span><span>.</span> <br>
          <span class="hps">In the construction</span> <span
            class="hps">of</span> <span class="hps">models</span> <span
            class="hps">of</span> <span class="hps">survival</span> <span
            class="hps">and</span> <span class="hps">growth</span> <span
            class="hps atn">(</span><span>via</span> <span class="hps">survModelComp</span>
          <span class="hps">and</span> <span class="hps">growthModelComp</span><span>)</span>
          <span class="hps">I get the following</span> <span
            class="hps">error</span><span>: <br>
            "Error</span> <span class="hps">in</span> <span
            class="hps">plot.window</span> <span class="hps atn">(</span><span>...</span><span>)</span><span>:
            need</span> <span class="hps">finite</span> <span
            class="hps atn">'</span><span>ylim</span><span>'</span> <span
            class="hps">values</span><br>
          <span class="hps">In</span> <span class="hps">addition:</span>
          <span class="hps">There</span> <span class="hps">were</span>
          <span class="hps">16</span> <span class="hps">warnings</span>
          <span class="hps atn">(</span><span>use warnings</span> <span
            class="hps atn">(</span><span>)</span> <span class="hps">to</span>
          <span class="hps">see</span> <span class="hps">them</span><span>)</span><span>."</span>
          <span class="hps"><br>
            Here </span><span class="hps">the code</span> <span
            class="hps">(which works</span> <span class="hps">well with</span>
          <span class="hps">other</span> populations<span>,</span> <span
            class="hps">except</span> <span class="hps">with</span> <span
            class="hps">this</span><span>)</span><span>:</span><br>
          <span class="hps">survModelComp</span> <span class="hps atn">(</span><span>dataf</span>
          <span class="hps">=</span> <span class="hps">dhsr</span><span>,</span>
          <span class="hps"></span><span class="hps">makePlot</span> <span
            class="hps">=</span> <span class="hps">TRUE</span><span>, </span><span
            class="hps">legendPos</span>  <span class="hps">=</span> <span
            class="hps atn">"</span><span>bottomleft</span><span>", </span><span
            class="hps">Maintitle</span>  <span class="hps">=</span> <span
            class="hps atn">"</span><span>Survival</span><span>"</span><span>)<br>
            It is possible that the many NAs create a problem?<br>
          </span><br>
          <span class="hps">2)</span> <span class="hps">in all </span></span><span
          id="result_box" lang="en"><span class="hps"><span
              id="result_box" lang="en"><span class="hps">analyzed</span>
              <span class="hps"></span></span> populations</span> <span
            class="hps">lambda</span> <span class="hps">get</span> <span
            class="hps">very high</span> <span class="hps">as many</span>
          <span class="hps">variables</span> <span class="hps">added</span>
          <span class="hps">in</span> <span class="hps">fecundity</span>
          <span class="hps">object</span><span>.</span> <br>
          <span class="hps">I tried</span> <span class="hps">inserting</span>
          <span class="hps">the</span> <span class="hps">data frame</span>
          <span class="hps">columns</span><span>:</span><br>
          <span class="hps">fec0</span> <span class="hps">(probability
            of</span> <span class="hps">flowering)</span><span>,</span>
          <span class="hps">fec1</span> <span class="hps">(number of</span>
          <span class="hps">fruits</span><span>)</span><span>,</span> <span
            class="hps">nFl</span> <span class="hps">(number of</span>
          <span class="hps">flowers</span><span>)</span><span>.</span><br>
          <span class="hps">I get a</span> <span class="hps">lambda</span><span>
            near </span><span class="hps">1</span> <span class="hps">only
            if</span> <span class="hps">I leave</span> <span
            class="hps">exclusively</span> <span class="hps">fec0</span>
          <span class="hps atn">(</span><span>the probability of</span>
          <span class="hps">flowering)</span><span>,</span> <span
            class="hps">does anyone know how</span> <span class="hps">to</span>
          <span class="hps">solve</span> <span class="hps">by adding</span>
          <span class="hps">at least</span> <span class="hps">fec1</span><span>?</span></span><br>
        R0 also get <span id="result_box" class="short_text" lang="en"><span
            class="hps">excessively high values... I think that is for
            the same problem with lambda.</span></span><br>
        <br>
        Thanks to all for any suggestion,<br>
        <br>
        Best wishes,<br>
        <br>
        Elena Sulis </div>
      <br>
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