Hello all,
     I am thinking about applying season::cosinor() analysis to some
irregularely spaced time series data. The data are unevenly spaced, so
usual time series methods, as well as the nscosinor() function are out. My
data do however trend over time and I am wondering if I can feed date as a
variable into my cosinor analyis.  In the example below, then I'd conclude
then that the abundances are seasonal, with maximal abundance in mid June
and furthermore, they are generally decreasing over time.
Can I use both time variables together like this? If not, is there some
better approach I should take?
Thanks in advance,
-Jacob

For context lAbundance is logg-odds transformed abundance data of a
microbial species in a given location over time.  RDate is the date the
sample was collected in the r date format.


> res <- cosinor(lAbundance ~ RDate, date = "RDate", data = lldata)

>summary(res)
Cosinor test
Number of observations = 62
Amplitude = 0.58
Phase: Month = June , day = 14
Low point: Month = December , day = 14
Significant seasonality based on adjusted significance level of 0.025  =
TRUE

>summary(res$glm)


Call:
glm(formula = f, family = family, data = data, offset = offset)

Deviance Residuals:
    Min       1Q   Median       3Q      Max
-2.3476  -0.6463   0.1519   0.6574   1.9618

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.0115693  1.8963070   0.006  0.99515
RDate       -0.0003203  0.0001393  -2.299  0.02514 *
cosw        -0.5516458  0.1837344  -3.002  0.00395 **
sinw         0.1762904  0.1700670   1.037  0.30423
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for gaussian family taken to be 0.9458339)

    Null deviance: 70.759  on 61  degrees of freedom
Residual deviance: 54.858  on 58  degrees of freedom
AIC: 178.36

Number of Fisher Scoring iterations: 2


llldata as a csv below
"RDate","lAbundance"
2003-03-12,-3.3330699059335
2003-05-21,-3.04104625745886
2003-06-17,-3.04734680029566
2003-07-02,-4.18791034708572
2003-09-18,-3.04419201802053
2003-10-22,-3.13805060873929
2004-02-19,-3.80688269144794
2004-03-17,-4.50755507726145
2004-04-22,-4.38846502542992
2004-05-19,-3.06618649442674
2004-06-17,-5.20518774876304
2004-07-14,-3.75041853151097
2004-08-25,-3.67882486716196
2004-09-22,-5.22205827512234
2004-10-14,-3.99297508670535
2004-11-17,-4.68793287601157
2004-12-15,-4.31712380781011
2005-02-16,-4.30893550479904
2005-03-16,-4.05781773988454
2005-05-11,-3.94746237402035
2005-07-19,-4.91195185391358
2005-08-17,-4.93590576323119
2005-09-15,-4.85820800095518
2005-10-20,-5.22956391101343
2005-12-13,-5.12244047315448
2006-01-18,-3.04854660925046
2006-02-22,-6.77145858348375
2006-03-29,-4.33151493849021
2006-04-19,-3.36152357710535
2006-06-20,-3.09071584142593
2006-07-25,-3.31430484483825
2006-08-24,-3.09974933041469
2006-09-13,-3.33288992218458
2007-12-17,-4.19942661980677
2008-03-19,-3.86146499633625
2008-04-22,-3.36161599919095
2008-05-14,-4.30878307213324
2008-06-18,-3.74372448768828
2008-07-09,-4.65951429661651
2008-08-20,-5.35984647704619
2008-09-22,-4.78481898261137
2008-10-20,-3.58588161980965
2008-11-20,-3.10625125552057
2009-02-18,-6.90675477864855
2009-03-11,-3.43446932013368
2009-04-23,-3.82688066341466
2009-05-13,-4.44885332005661
2009-06-18,-3.97671552612412
2009-07-09,-3.40185954003936
2009-08-19,-3.44958231694091
2009-09-24,-3.86508161094726
2010-01-28,-4.95281587967569
2010-02-11,-3.78064756876257
2010-03-24,-3.5823501176064
2010-04-27,-4.33635715879999
2010-05-17,-3.90545735473055
2010-07-21,-3.3147176517321
2010-08-11,-4.53218360860017
2010-10-21,-6.90675477864855
2010-11-23,-6.90675477864855
2010-12-16,-6.75158176094352
2011-01-11,-6.90675477864855

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