[R] Excel Trend Function

[Daniel Malter]

Hi, I would be careful with imputing values. Imputing is a disputed practice.
Also, you seem to have huge variation in your data with a nonlinear trend. 
Since your data is time series data, you may consider modeling the time
series and then to predict n-time periods ahead and use these predicted
values (look up arima and garch models for that, which are the most common).
An alternative approach would be to fit a smoothing spline (package mgcv,
function gam() ) through your time trend (leave out the missing data) and
then predict for your missing data periods.

BUT: Are you sure that your weeks 19 to 25 are correctly recorded? To
predict weeks 17, 18, and 26 looks  particularly odd given the observations
you have for 19 to 25. 17, 18, and 26 could either be connected to the trend
from the previous observation, i.e. be nonzero for 17 and 18, and zero for
26, or they also could be "connected" to the following observation and be
zero for 17 and 18, and nonzero for 26. This is because the plain zeros in
19-25 are really odd. Are you sure that the observation was a definitve
zero? If so, it does not make imputation look like a good strategy for these
three values.

For period 46 prediction with a time series model looks more promising, but
the question here is, is it necessary (as it is the last observation
anyway)? You may just want to avoid doing something wrong by using an error
prone prediction for your last period.

Just my two cents,
Daniel



Felipe Carrillo wrote:
> 
> Hi:
> I have a dataset and need to interpolate for missing days. In Excel I
> either average from sampled days from above and below the missing days or
> use the TREND function to make up for the missing values. I have been
> reading about na.approx, is this function similar to the TREND function?
> Which is the best recommendable way to make up for missing data?
> Here's my dataset: weeks 17,18,26 and 46 have 0 daysSamp.
> 
> Year	Week daysSamp     Lower	TotalPD	Upper	varTotalPD
> 2006	47	6	126988	188259	249530	1045878675
> 2006	48	7	189155	253350	317545	1148102355
> 2006	49	7	103300	132741	162182	241480186
> 2006	50	6	11801	252576	493352	16151006813
> 2006	51	7	2348	3671	4994	487926
> 2006	52	5	2606	29901	57196	215454181
> 2006	2	7	2968	4513	6058	664723
> 2006	3	7	1128	1889	2650	161231
> 2006	4	7	479	963	1447	65196
> 2006	5	7	2819	4413	6007	708094
> 2006	6	6	-1009	3128	7264	4766743
> 2006	7	7	-5239	10769	26777	71387835
> 2006	8	7	150	503	856	34685
> 2006	9	7	1858	2989	4120	356562
> 2006	10	7	193	494	795	25281
> 2006	11	7	125	346	567	13627
> 2006	12	7	432	767	1102	31189
> 2006	13	7	1229	1867	2505	113569
> 2006	14	7	813	1339	1865	77140
> 2006	15	4	-66	124	315	10105
> 2006	16	7	152	903	1654	157242
> 2006	17	0	
> 2006	18	0	
> 2006	19	5	0	0	0	0
> 2006	20	4	0	0	0	0
> 2006	21	5	0	0	0	0
> 2006	22	6	0	0	0	0
> 2006	23	7	-65	285	635	34112
> 2006	24	6	0	0	0	0
> 2006	25	7	0	0	0	0
> 2006	26	0				
> 2006	27	4	228	931	1634	137726
> 2006	28	4	801	2231	3662	569977
> 2006	29	4	4544	9242	13939	6147522
> 2006	30	5	15798	28465	41131	44697915
> 2006	31	5	25398	41049	56701	68245523
> 2006	32	5	48197	82216	116235	322416917
> 2006	33	5	142980	230411	317841	2129630128
> 2006	34	5	227141	360468	493794	4952314336
> 2006	35	5	467244	756325	1045405	23281569629
> 2006	36	5	281049	463331	645614	9256900449
> 2006	37	2	227636	620330	1013023	42961663047
> 2006	38	3	478990	983472	1487954	70903343603
> 2006	39	7	539690	846522	1153354	26228718974
> 2006	40	7	320959	457866	594773	5221891252
> 2006	41	7	427561	582452	737343	6683813344
> 2006	42	7	271788	351103	430418	1752614293
> 2006	43	7	165019	208853	252687	535301133
> 2006	44	7	91514	117390	143266	186537178
> 2006	45	7	59061	79187	99313	112842787
> 2006	46	0	
> 
> Felipe D. Carrillo
> Supervisory Fishery Biologist
> Department of the Interior  
> US Fish & Wildlife Service
>   California, USA
> 
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 
> 

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