N.C. Matalas
1962
<p><span>A </span><span class="ScopusTermHighlight">statistical</span><span> analysis is made of the sequences of annual </span><span class="ScopusTermHighlight">tree</span><span> </span><span class="ScopusTermHighlight">ring</span><span> widths and indices. The expected value of growth during any year is shown to be proportional to the standard deviation of the growth, so that the coefficient of variation is a measure of the sensitivity of the growth of a </span><span class="ScopusTermHighlight">tree</span><span>. </span><span class="ScopusTermHighlight">Tree</span><span> </span><span class="ScopusTermHighlight">ring</span><span> </span><span class="ScopusTermHighlight">data</span><span> were found to be non-randomly distributed in time. The large values of serial correlation indicated that the non-randomness cannot be attributed entirely to climatic factors. Correlogram and power spectrum analyses applied to a sequence of </span><span class="ScopusTermHighlight">tree</span><span> </span><span class="ScopusTermHighlight">ring</span><span> indices for a pinyon pine showed that the </span><span class="ScopusTermHighlight">data</span><span> were generated by an autoregressive process. The </span><span class="ScopusTermHighlight">statistical</span><span> parameter measuring the sensitivity or complacency of growth is used to derive a growth function. </span></p>
application/pdf
10.1080/02626666209493254
en
Taylor & Francis
Statistical properties of tree ring data
article