Dear Sir,
After installing prospectr,
> data(NIRsoil)> mode(NIRsoil)[1] "list">
I am a beginner and the structure of “NIRsoil” is complicated.
Judging from the explanation of NIRsoil (see below), there are six elements:
NT, Ciso, CEC, train, validation, spc.
Please tell me how to know the structure of such “NIRsoil”.
When using mode (NIRsoil) , The answer is just a “list”.
Is there a command or function "Detailstructure (NIRsoil)"?
> NIRsoil
.
. spc.2494 spc.2496 spc.24981 0.3724227 0.3724588 0.37256772
0.3159643 0.3164802 0.31681803 0.3416802 0.3422180 0.34263164 0.3650448
0.3654987 0.36580555 0.3050233 0.3058226 0.30640076 0.3599009 0.3603650
0.36070207 0.3365467 0.3369826 0.33725788 0.3922267 0.3926329 0.39288209
0.3149452 0.3153307 0.315540410 0.4951153 0.4954152 0.495766411 0.3414548
0.3418657 0.342114012 0.3314737 0.3319690 0.332336513 0.4153854 0.4156993
0.416079614 0.3311567 0.3316245 0.331926815 0.3289777 0.3294281 0.329720616
0.4268982 0.4274236 0.427819517 0.3421552 0.3426531 0.342981518 0.3452011
0.3457459 0.346121719 0.3497368 0.3497175 0.349840320 0.3896840 0.3901652
0.390537521 0.4062244 0.4066894 0.407021322 0.3792031 0.3796499 0.379960123
0.3252305 0.3256037 0.325836624 0.3427994 0.3431511 0.343363125 0.3410443
0.3414203 0.341648926 0.3947710 0.3952165 0.395562027 0.2930943 0.2934901
0.293697728 0.4138924 0.4144398 0.414861929 0.2906964 0.2910948 0.291324130
0.4000607 0.4004497 0.400749131 0.3275807 0.3278961 0.328067632 0.3343273
0.3347059 0.334947033 0.2923162 0.2927208 0.292952534 0.3181143 0.3184221
0.318574835 0.3959161 0.3963806 0.396695436 0.3412020 0.3415608 0.341737737
0.3109980 0.3119904 0.312796538 0.3452408 0.3457109 0.346040139 0.2352630
0.2357922 0.236104440 0.3731434 0.3735985 0.373948341 0.3776968 0.3780733
0.378314142 0.4279117 0.4278319 0.427811343 0.3499106 0.3502492 0.350448044
0.4060152 0.4064416 0.406781645 0.4434104 0.4437352 0.444117646 0.3106347
0.3111292 0.311479047 0.3048005 0.3052686 0.305555748 0.3074032 0.3078929
0.308188549 0.3099467 0.3103620 0.310607950 0.4140719 0.4140101 0.414070551
0.3047789 0.3051992 0.305453152 0.4372076 0.4371921 0.437301153 0.3784582
0.3788292 0.379046054 0.3070685 0.3074959 0.307739255 0.3929690 0.3930495
0.393248956 0.3104950 0.3109303 0.311175657 0.3110389 0.3114884 0.311783658
0.3561086 0.3565895 0.356935659 0.2946499 0.2950254 0.295230760 0.3396696
0.3402275 0.340604561 0.4174463 0.4174852 0.417609462 0.3838490 0.3845536
0.385175463 0.4214520 0.4217800 0.422008564 0.3136719 0.3141062 0.314410265
0.3137282 0.3141668 0.314444466 0.4341556 0.4341235 0.434172067 0.3028214
0.3032053 0.303438768 0.2929183 0.2933525 0.293613269 0.2901444 0.2905667
0.290814470 0.2926482 0.2930853 0.293328871 0.3964101 0.3968658 0.397207272
0.3205706 0.3209653 0.321186973 0.2965653 0.2970253 0.297328574 0.3271259
0.3274269 0.327623075 0.2910520 0.2914549 0.291697476 0.3266725 0.3271569
0.327475777 0.3405427 0.3410150 0.341319778 0.3164929 0.3169560 0.317269479
0.3489597 0.3495394 0.349918280 0.3369682 0.3374025 0.337660681 0.2608885
0.2613245 0.261581182 0.3132109 0.3136024 0.313788183 0.3155325 0.3159175
0.316144884 0.3156847 0.3160608 0.316250785 0.2751068 0.2754884 0.275712986
0.2722970 0.2726988 0.272900087 0.3421156 0.3424138 0.342577688 0.4408897
0.4413919 0.441767389 0.4094418 0.4098032 0.410052590 0.2883307 0.2887366
0.288972191 0.3368085 0.3373375 0.337674492 0.2914632 0.2918586 0.292056993
0.3701615 0.3703609 0.370657894 0.3168159 0.3172900 0.317585795 0.3141627
0.3145356 0.314785296 0.2717998 0.2721882 0.272409297 0.2994829 0.2998522
0.300074998 0.4238313 0.4238643 0.423967099 0.3173946 0.3178398 0.3181364100
0.3065352 0.3070051 0.3073053101 0.4119025 0.4122178 0.4126194102 0.2997539
0.3001756 0.3004323103 0.3195902 0.3200457 0.3203547104 0.3770273 0.3775299
0.3779288105 0.3119653 0.3123196 0.3125118106 0.3007703 0.3012067 0.3014555107
0.3583141 0.3586335 0.3588411108 0.3613160 0.3616626 0.3619002109 0.3012548
0.3016973 0.3019971110 0.3040114 0.3044745 0.3047490111 0.3886676 0.3889934
0.3894869112 0.3381325 0.3386472 0.3389995113 0.3228837 0.3232841 0.3235284114
0.3175641 0.3179575 0.3182012115 0.3255604 0.3259808 0.3262322116 0.3038366
0.3043306 0.3046326117 0.3040762 0.3045244 0.3048216118 0.3101427 0.3105674
0.3108223119 0.3186323 0.3190890 0.3194055120 0.3183660 0.3188377 0.3191515121
0.3716398 0.3723766 0.3729757122 0.3336347 0.3341000 0.3344247123 0.3013631
0.3017261 0.3018954124 0.3559751 0.3563222 0.3565449125 0.3467284 0.3475789
0.3482055126 0.2983477 0.2992734 0.3000016127 0.2966113 0.2970161 0.2972673128
0.3244559 0.3249162 0.3252265129 0.3687044 0.3692860 0.3697534130 0.2949226
0.2953484 0.2956104131 0.3449411 0.3454331 0.3457713132 0.3458079 0.3462659
0.3465872133 0.3879239 0.3882694 0.3884915134 0.3998409 0.3997933 0.3999189135
0.2591648 0.2596039 0.2598299136 0.3145797 0.3149986 0.3152637137 0.3184437
0.3188738 0.3191448138 0.3101936 0.3105727 0.3108114139 0.3263323 0.3267737
0.3270491140 0.3234212 0.3238232 0.3240880141 0.5669109 0.5681474 0.5693322142
0.4268930 0.4277861 0.4285390 [ reached getOption("max.print") -- 683
Finally, another question: Why 142 lines ? 825
observed data and 5 variables, the reference said.
Reference-----------
| NIRsoil {prospectr} | R Documentation |
NIRSoil
Description
Soil spectral library of the ‘Chimiometrie 2006’challenge. The database
contains absorbance spectra ofdried and sieved soil samples measured between
1100 nm and2498 nm at 2 nm interval. The soil samples come fromagricultural
fields collected from all over the Walloonregion in Belgium. Three parameters
are associated with thespectral library: Nt (Total Nitrogen in g/Kg of dry
soil),CEC (Cation Exchange Capacity in meq/100 g of dry soil) andCiso (Carbon
in g/100 g of dry soil). Carbon content hasbeen measured following the ISO14235
method.
Usage
data(NIRsoil)
Format
A data frame of 825 observations and 5 variables
Details
The dataset includes 618 training and 207 test samples with5 variables: Nt
(Total Nitrogen), Ciso (Carbon), CEC(Cation Exchange Capacity), train (vector
of 0,1indicating training (1) and validation (0) samples) and spc(a matrix with
absorbance NIR data and bandpositions as colnames). Nt, Ciso and CEC
haverespectively 22 %, 11 % and 46 % of the observationswith missing values.
Source
Pierre Dardenne from Walloon Agricultural Research Centre,Belgium.
References
Fernandez Pierna, J.A., and Dardenne, P., 2008. Soilparameter quantification by
NIRS as a Chemometric challengeat 'Chimiometrie 2006'. Chemometrics and
IntelligentLaboratory Systems 91, 94-98.Minasny, B., and McBratney, A.B., 2008.
Regression rules asa tool for predicting soil properties from
infraredreflectance spectroscopy. Chemometrics and IntelligentLaboratory
Systems 94, 72-79.
Package prospectr version 0.1.3 Index
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