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Two population Global Testing procedure

Global2.Rd

The function implements the Global Testing procedure for testing mean differences between two functional populations. Functional data are tested locally and unadjusted and adjusted p-value functions are provided. The unadjusted p-value function controls the point-wise error rate. The adjusted p-value function controls the interval-wise error rate.

Usage

Global2(
  data1,
  data2,
  mu = 0,
  B = 1000L,
  paired = FALSE,
  dx = NULL,
  stat = "Integral"
)

Arguments

data1

First population's data. Either pointwise evaluations of the functional data set on a uniform grid, or a fd object from the package fda. If pointwise evaluations are provided, data2 is a matrix of dimensions c(n1,J), with J evaluations on columns and n1 units on rows.

data2

Second population's data. Either pointwise evaluations of the functional data set on a uniform grid, or a fd object from the package fda. If pointwise evaluations are provided, data2 is a matrix of dimensions c(n1,J), with J evaluations on columns and n2 units on rows.

mu

Functional mean difference under the null hypothesis. Three possibilities are available for mu: a constant (in this case, a constant function is used); a J-dimensional vector containing the evaluations on the same grid which data are evaluated; a fd object from the package fda containing one function. The default is mu=0.

B

The number of iterations of the MC algorithm to evaluate the p-values of the permutation tests. The defualt is B=1000.

paired

A logical indicating whether a paired test has to be performed. Default is FALSE.

dx

Used only if a fd object is provided. In this case, dx is the size of the discretization step of the grid used to evaluate functional data. If set to NULL, a grid of size 100 is used. Default is NULL.

stat

Test statistic used for the global test. Possible values are: "Integral": integral of the squared sample mean difference; "Max": maximum of the squared sample mean difference; "Integral_std": integral of the squared t-test statistic; "Max_std": maximum of the squared t-test statistic. Default is "Integral".

Value

An object of class fdatest2, containing the following components:

  • test: String vector indicating the type of test performed. In this case equal to "2pop".

  • mu: Evaluation on a grid of the functional mean difference under the null hypothesis (as entered by the user).

  • unadjusted_pval: Evaluation on a grid of the unadjusted p-value function (it is a constant function according to the global testing procedure).

  • adjusted_pval: Evaluation on a grid of the adjusted p-value function.

  • data.eval: Evaluation on a grid of the functional data.

  • ord_labels: Vector of labels indicating the group membership of data.eval.

References

A. Pini and S. Vantini (2017). The Interval Testing Procedure: Inference for Functional Data Controlling the Family Wise Error Rate on Intervals. Biometrics 73(3): 835–845.

Pini, A., & Vantini, S. (2017). Interval-wise testing for functional data. Journal of Nonparametric Statistics, 29(2), 407-424

See also

See also IWT2 for local inference. See plot.fdatest2 for plotting the results.

Examples

# Importing the NASA temperatures data set
data(NASAtemp)

# Performing the Global for two populations
Global.result <- Global2(NASAtemp$paris, NASAtemp$milan)

# Plotting the results of the Global
plot(
  Global.result, 
  xrange = c(0, 12), 
  main = 'Global results for testing mean differences'
)



# Selecting the significant components at 5% level
which(Global.result$adjusted_pval < 0.05)
#>   [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
#>  [19]  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
#>  [37]  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
#>  [55]  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
#>  [73]  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
#>  [91]  91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107 108
#> [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
#> [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
#> [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
#> [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
#> [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198
#> [199] 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216
#> [217] 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234
#> [235] 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252
#> [253] 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270
#> [271] 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288
#> [289] 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306
#> [307] 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324
#> [325] 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342
#> [343] 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360
#> [361] 361 362 363 364 365